Memory evaluation method and apparatus

ABSTRACT

A memory evaluation method and apparatus are provided. The method includes: determining a health degree evaluation model indicating a relationship in which a health degree of a memory changes with at least one health degree influencing factor of the memory; obtaining at least one running parameter value corresponding to each of the at least one health degree influencing factor; separately matching the at least one running parameter value corresponding to each health degree influencing factor to the health degree evaluation model, to obtain the health degree of the memory; and outputting health degree indication information which indicate whether the memory needs to be replaced. Therefore, the memory is not faulty and the health degree of the memory is a relatively low, a user is prompted to replace the memory.

CROSS-REFERENCE TO RELATED APPLICATION

This application is a continuation of International Application No.PCT/CN2018/087360, filed on May 17, 2018, which claims priority toChinese Patent Application No. 201710841912.5, filed on Sep. 18, 2017.The disclosures of the aforementioned applications are herebyincorporated by reference in their entireties.

TECHNICAL FIELD

Embodiments of the present application relate to the field of computertechnologies, and in particular, to a memory evaluation method andapparatus.

BACKGROUND

With development of an internet technology (IT), a total capacity of amemory of a server is increasingly large, so that normal working of thememory is more important than normal running of the server. Therefore,to support normal running of the server, whether working of the memoryis normal needs to be determined before the memory is faulty.

In the prior art, for some servers such as an x86 server, whether amemory can work normally is usually determined based on whether thememory is available, whether the server can normally identify thememory, whether an uncorrectable error (UCE) occurs in the memory, orthe like. In other words, whether the memory can work normally isdetermined based on whether the memory is faulty. After it is determinedthat the memory of the server is faulty, a user is prompted to replacethe faulty memory.

An existing problem is as follows: In the prior art, when it isdetermined, based on whether the memory is faulty, whether the memorycan work normally, a fault of the memory has affected normal running ofthe server. For example, when it is determined that the memory isunavailable, the memory has caused severe impact such as breakdown,service impairment, and even data loss of the server.

SUMMARY

This application provides a memory evaluation method and apparatus, toevaluate a health degree of a memory in a server, and to prompt a userto replace the memory when the memory is not faulty and has a relativelylow health degree, so that the memory can support normal running of theserver.

To achieve the foregoing objectives, the following technical solutionsare used in this application.

According to a first aspect, a memory evaluation method is provided. Themethod includes: determining a health degree evaluation model of ato-be-evaluated memory, where the health degree evaluation model is arelationship in which a health degree of the to-be-evaluated memorychanges with at least one health degree influencing factor of theto-be-evaluated memory, one health degree influencing factor correspondsto one running parameter and one failure rate parameter, and one healthdegree influencing factor corresponds to one weight, where the weight isa constant; obtaining at least one running parameter value correspondingto each of the at least one health degree influencing factor, where theat least one running parameter value corresponds to one runningparameter; separately matching the at least one running parameter valuecorresponding to each health degree influencing factor to the healthdegree evaluation model, to obtain the health degree of theto-be-evaluated memory; and outputting health degree indicationinformation of the to-be-evaluated memory based on the health degree ofthe to-be-evaluated memory, where the health degree indicationinformation of the to-be-evaluated memory is used to indicate, to auser, whether the to-be-evaluated memory needs to be replaced.

It should be noted that this application provides the health degreeevaluation model that describes the relationship in which the healthdegree of the to-be-evaluated memory changes with the at least onehealth degree influencing factor of the to-be-evaluated memory, so thata memory evaluation apparatus can obtain the health degree of theto-be-evaluated memory based on the health degree evaluation model ofthe to-be-evaluated memory. Therefore, the memory evaluation apparatuscan generate the health degree indication information of theto-be-evaluated memory based on a value of the health degree of theto-be-evaluated memory. To be specific, before the to-be-evaluatedmemory is faulty, the memory evaluation apparatus can determine, basedon the health degree of the to-be-evaluated memory, whether to replacethe to-be-evaluated memory. In addition, the memory evaluation apparatuscan output the health degree indication information of theto-be-evaluated memory when the memory is not faulty and the healthdegree of the memory is relatively low, to prompt the user to replacethe memory, so that the memory can support normal running of the server.

In addition, the weight corresponding to one health degree influencingfactor can indicate an extent to which the health degree influencingfactor affects the health degree of the to-be-evaluated memory, andhealth degree influencing factors corresponding to different weightshave different impact on the health degree of the to-be-evaluatedmemory. For example, a larger weight corresponding to a health degreeinfluencing factor indicates greater impact of the health degreeinfluencing factor on the health degree of the to-be-evaluated memory.In this way, a weight corresponding to each health degree influencingfactor in the health degree evaluation model provided in thisapplication can indicate impact of each health degree influencing factoron the health degree of the to-be-evaluated memory, so that impactextents of different health degree evaluation factors for theto-be-evaluated memory in the health degree evaluation model are moreproper for the to-be-evaluated memory. This helps to accurately evaluatethe health degree of the to-be-evaluated memory.

In a possible implementation, the separately matching the at least onerunning parameter value corresponding to each health degree influencingfactor to the health degree evaluation model, to obtain the healthdegree of the to-be-evaluated memory may include: separately matchingthe at least one running parameter value corresponding to each healthdegree influencing factor to a first submodel of the correspondinghealth degree influencing factor in the health degree evaluation model,to obtain a health degree impairment value corresponding to each healthdegree influencing factor, where the health degree evaluation modelincludes a second submodel and a first submodel that corresponds to eachhealth degree influencing factor, a first submodel of one health degreeinfluencing factor is a relationship between a health degree impairmentvalue corresponding to the health degree influencing factor and arunning parameter and failure rate parameter corresponding to the healthdegree influencing factor, and the second submodel is a relationship inwhich the health degree of the to-be-evaluated memory changes with thehealth degree impairment value corresponding to each health degreeinfluencing factor and a relationship in which the health degree of theto-be-evaluated memory changes with a weight corresponding to eachhealth degree influencing factor; and obtaining the health degree of theto-be-evaluated memory based on the health degree impairment valuecorresponding to each health degree influencing factor, the weightcorresponding to each health degree influencing factor, and the secondsubmodel.

It should be noted that the memory evaluation apparatus provided in thisapplication can obtain, based on the first submodel corresponding toeach health degree influencing factor in the health degree evaluationmodel, the health degree impairment value that is of the to-be-evaluatedmemory and that corresponds to each health degree influencing factor, toindicate impact of each health degree influencing factor on the healthdegree of the to-be-evaluated memory. In addition, the health degreeimpairment value corresponding to each health degree influencing factorand the weight corresponding to each health degree influencing factorare separately matched to the second submodel, to obtain the healthdegree of the to-be-evaluated memory affected by health degreeinfluencing factors corresponding to different weights (differentweights). In this way, different health degree evaluation models can begenerated for different to-be-evaluated memories. This helps to increaseaccuracy of the health degree, of the to-be-evaluated memory, obtainedbased on the health degree evaluation model.

In a possible implementation, the at least one health degree influencingfactor includes one or more of the following: a memory runningtemperature factor, a memory service load factor, a total memory runningduration factor, a memory swap factor, a memory correctable error CEfrequency factor, a memory uncorrectable error UCE frequency factor, anda memory performance attenuation factor.

A plurality of health degree influencing factors are preset in thehealth degree evaluation model provided in this application, so that theuser can select corresponding health degree influencing factors fordifferent to-be-evaluated memories. In this way, a health degreeevaluation factor for the to-be-evaluated memory in the health degreeevaluation model is more proper for the to-be-evaluated memory. Thishelps to accurately evaluate the health degree of the to-be-evaluatedmemory.

In a possible implementation, a running parameter corresponding to thememory running temperature factor is a running temperature of theto-be-evaluated memory; a running parameter corresponding to the memoryservice load factor is a quantity of charging/discharging times of theto-be-evaluated memory; a running parameter corresponding to the totalmemory running duration factor is total running duration of theto-be-evaluated memory; a running parameter corresponding to the memoryswap factor is a quantity of swap times of the to-be-evaluated memory; arunning parameter corresponding to the memory CE frequency factor is aquantity of CEs of the to-be-evaluated memory and/or a CE frequency ofthe to-be-evaluated memory; a running parameter corresponding to thememory UCE frequency factor is a quantity of UCEs of the to-be-evaluatedmemory and/or a UCE frequency of the to-be-evaluated memory; and arunning parameter corresponding to the memory performance attenuationfactor is a performance value attenuation magnitude of theto-be-evaluated memory.

It should be noted that the memory evaluation apparatus provided in thisapplication can store data that describes a relationship between arunning parameter and a failure rate parameter that correspond to eachhealth degree influencing factor, for example, a curve that describeshow a failure rate parameter of the to-be-evaluated memory changes witha corresponding running parameter. The curve that describes how afailure rate parameter of the to-be-evaluated memory changes with acorresponding running parameter is data pre-obtained through statisticscollection. In this way, the memory evaluation apparatus can evaluate,based on existing data obtained through statistics collection, thehealth degree of the to-be-evaluated memory that is not yet faulty.

In a possible implementation, each of the at least one health degreeinfluencing factor included in the health degree evaluation modelcorresponds to one algorithm, where the algorithm may be addition and/ormultiplication. The “obtaining the health degree of the to-be-evaluatedmemory based on the health degree impairment value corresponding to eachhealth degree influencing factor, the weight corresponding to eachhealth degree influencing factor, and the second submodel” may include:obtaining the health degree of the to-be-evaluated memory based on thehealth degree impairment value corresponding to each health degreeinfluencing factor, the weight corresponding to each health degreeinfluencing factor, the second submodel, and the algorithm correspondingto each health degree influencing factor.

For one memory in the memory evaluation apparatus, that is, one memoryin the server, while quantizing impact of each health degree influencingfactor of the memory on a health degree of the memory based on a weightcorresponding to the health degree influencing factor, the memoryevaluation apparatus can further quantize an extent to which each healthdegree influencing factor affects the health degree of the memory, basedon an algorithm corresponding to the health degree influencing factor.This helps to increase accuracy of the health degree of theto-be-evaluated memory.

In a possible implementation, the outputting health degree indicationinformation of the to-be-evaluated memory based on the health degree ofthe to-be-evaluated memory may include: outputting first health degreeindication information when a value of the health degree of theto-be-evaluated memory is within a first preset value range, where thefirst health degree indication information is used to indicate, to theuser, that the to-be-evaluated memory does not need to be replaced;outputting second health degree indication information when a value ofthe health degree of the to-be-evaluated memory is within a secondpreset value range, where the second health degree indicationinformation is used to indicate, to the user, that the to-be-evaluatedmemory is replaceable; or outputting third health degree indicationinformation when a value of the health degree of the to-be-evaluatedmemory is within a third preset value range, where the third healthdegree indication information is used to indicate, to the user, that theto-be-evaluated memory needs to be replaced.

It should be noted that in the memory evaluation method provided in thisapplication, in a process of displaying the health degree indicationinformation of the to-be-evaluated memory to the user, the memoryevaluation apparatus may display different health degree indicationinformation for to-be-evaluated memories with different health degreevalues. In this way, when the to-be-evaluated memory is not faulty andthe health degree of the memory is relatively low (the value of thehealth degree is relatively small), the memory evaluation apparatus canprompt the user to replace the to-be-evaluated memory, so that theto-be-evaluated memory supports normal running of the server.

In a possible implementation, the determining a health degree evaluationmodel of a to-be-evaluated memory includes: receiving the at least onehealth degree influencing factor that is set by the user; determiningthe at least one health degree influencing factor that is set by theuser, as a health degree influencing factor included in the healthdegree evaluation model of the to-be-evaluated memory; determining acorresponding first submodel based on the at least one health degreeinfluencing factor; receiving the weight and the algorithm thatcorrespond to each of the at least one health degree influencing factorthat is set by the user; and determining the second submodel based onthe weight and the algorithm that correspond to each health degreeinfluencing factor.

It should be noted that, different to-be-evaluated memories may havedifferent health degree influencing factors, and data about how failurerate parameters corresponding to health degree influencing factors ofdifferent to-be-evaluated memories change with corresponding runningparameters may be different. Therefore, health degree evaluation modelscorresponding to different to-be-evaluated memories may be different. Inthe memory evaluation method provided in this embodiment of the presentapplication, the memory evaluation apparatus can determine firstsubmodels corresponding to health degree influencing factors fordifferent to-be-evaluated memories and second submodels for theto-be-evaluated memories, that is, determine health degree evaluationmodels for different to-be-evaluated memories. In this way, the healthdegree evaluation model provided in this embodiment of the presentapplication can be proper for the to-be-evaluated memory. This helps toincrease accuracy of the health degree, of the to-be-evaluated memory,obtained based on the health degree evaluation model.

In a possible implementation, before the health degree indicationinformation of the to-be-evaluated memory is generated based on thehealth degree of the to-be-evaluated memory, the memory evaluationmethod provided in this application further includes: receiving thefirst preset value range, the second preset value range, and the thirdpreset value range that are set by the user.

It should be noted that, according to the memory evaluation methodprovided in this application, the user can set different preset valueranges for different to-be-evaluated memories, so that the health degreeindication information that is of the to-be-evaluated memory and that isobtained by the memory evaluation apparatus based on the preset valuerange is more proper for the to-be-evaluated memory. This helps to moreaccurately indicate, to the user, whether the to-be-evaluated memoryneeds to be replaced.

In a possible implementation, after the running parameter valuecorresponding to each health degree influencing factor is separatelyinput to the health degree evaluation model, to obtain the health degreeof the to-be-evaluated memory, the memory evaluation method provided inthis application further includes: receiving template data that is ofthe to-be-evaluated memory and that is updated by the user, where thetemplate data includes at least one or more of the following: the atleast one health degree influencing factor, the running parametercorresponding to each of the at least one health degree influencingfactor, the weight corresponding to each health degree influencingfactor, the algorithm corresponding to each health degree influencingfactor, the first preset value range, the second preset value range, andthe third preset value range; and updating the health degree evaluationmodel based on the updated template data of the to-be-evaluated memory.

Because the user can update the health degree evaluation model of theto-be-evaluated memory, so that the health degree evaluation model ismore proper for the to-be-evaluated memory, the health degree that is ofthe to-be-evaluated memory and that is obtained by the memory evaluationapparatus based on the updated health degree evaluation model is moreaccurate for the to-be-evaluated memory. This helps to more accuratelyindicate, to the user, whether the to-be-evaluated memory needs to bereplaced.

According to a second aspect, this application provides a memoryevaluation apparatus. The apparatus includes a determining module, anobtaining module, a matching module, and an output module. Thedetermining module is configured to determine a health degree evaluationmodel of a to-be-evaluated memory. The health degree evaluation model isa relationship in which a health degree of the to-be-evaluated memorychanges with at least one health degree influencing factor of theto-be-evaluated memory, one health degree influencing factor correspondsto one running parameter and one failure rate parameter, and one healthdegree influencing factor corresponds to one weight, where the weight isa constant. The obtaining module is configured to obtain at least onerunning parameter value that corresponds to each of the at least onehealth degree influencing factor determined by the determining module,where the at least one running parameter value corresponds to onerunning parameter. The matching module is configured to separatelymatch, to the health degree evaluation model, the at least one runningparameter value that corresponds to each health degree influencingfactor and that is obtained by the obtaining module, to obtain thehealth degree of the to-be-evaluated memory. The output module isconfigured to output health degree indication information of theto-be-evaluated memory based on the health degree that is of theto-be-evaluated memory and that is obtained by the matching module,where the health degree indication information of the to-be-evaluatedmemory is used to indicate, to a user, whether the to-be-evaluatedmemory needs to be replaced.

In a possible implementation, the matching module is specificallyconfigured to: separately match the at least one running parameter valuecorresponding to each health degree influencing factor to a firstsubmodel of the corresponding health degree influencing factor in thehealth degree evaluation model, to obtain a health degree impairmentvalue corresponding to each health degree influencing factor, where thehealth degree evaluation model includes a second submodel and a firstsubmodel that corresponds to each health degree influencing factor, afirst submodel of one health degree influencing factor is a relationshipbetween a health degree impairment value corresponding to the healthdegree influencing factor and a running parameter and failure rateparameter corresponding to the health degree influencing factor, and thesecond submodel is a relationship in which the health degree of theto-be-evaluated memory changes with the health degree impairment valuecorresponding to each health degree influencing factor and arelationship in which the health degree of the to-be-evaluated memorychanges with a weight corresponding to each health degree influencingfactor; and obtain the health degree of the to-be-evaluated memory basedon the health degree impairment value corresponding to each healthdegree influencing factor, the weight corresponding to each healthdegree influencing factor, and the second submodel.

In a possible implementation, the at least one health degree influencingfactor includes one or more of the following: a memory runningtemperature factor, a memory service load factor, a total memory runningduration factor, a memory swap factor, a memory correctable error CEfrequency factor, a memory uncorrectable error UCE frequency factor, anda memory performance attenuation factor.

In a possible implementation, a running parameter corresponding to thememory running temperature factor is a running temperature of theto-be-evaluated memory; a running parameter corresponding to the memoryservice load factor is a quantity of charging/discharging times of theto-be-evaluated memory; a running parameter corresponding to the totalmemory running duration factor is total running duration of theto-be-evaluated memory; a running parameter corresponding to the memoryswap factor is a quantity of swap times of the to-be-evaluated memory; arunning parameter corresponding to the memory CE frequency factor is aquantity of CEs of the to-be-evaluated memory and/or a CE frequency ofthe to-be-evaluated memory; a running parameter corresponding to thememory UCE frequency factor is a quantity of UCEs of the to-be-evaluatedmemory and/or a UCE frequency of the to-be-evaluated memory; and arunning parameter corresponding to the memory performance attenuationfactor is a performance value attenuation magnitude of theto-be-evaluated memory.

In a possible implementation, each of the at least one health degreeinfluencing factor included in the health degree evaluation modelcorresponds to one algorithm, where the algorithm may be addition and/ormultiplication. The matching module is further configured to obtain thehealth degree of the to-be-evaluated memory based on the health degreeimpairment value corresponding to each health degree influencing factor,the weight corresponding to each health degree influencing factor, thesecond submodel, and the algorithm corresponding to each health degreeinfluencing factor.

In a possible implementation, the output module is specificallyconfigured to: output first health degree indication information when avalue of the health degree of the to-be-evaluated memory is within afirst preset value range, where the first health degree indicationinformation is used to indicate, to the user, that the to-be-evaluatedmemory does not need to be replaced; output second health degreeindication information when a value of the health degree of theto-be-evaluated memory is within a second preset value range, where thesecond health degree indication information is used to indicate, to theuser, that the to-be-evaluated memory is replaceable; or output thirdhealth degree indication information when a value of the health degreeof the to-be-evaluated memory is within a third preset value range,where the third health degree indication information is used toindicate, to the user, that the to-be-evaluated memory needs to bereplaced.

In a possible implementation, the determining module includes areceiving submodule and a determining submodule. The receiving submoduleis configured to receive the at least one health degree influencingfactor that is set by the user. The determining submodule is configuredto: determine the at least one health degree influencing factor that isset by the user and that is received by the receiving submodule, as ahealth degree influencing factor included in the health degreeevaluation model of the to-be-evaluated memory; and determine acorresponding first submodel based on the at least one health degreeinfluencing factor. The receiving submodule is further configured toreceive the weight and the algorithm that correspond to each of the atleast one health degree influencing factor that is set by the user. Thedetermining submodule is further configured to determine the secondsubmodel based on the weight and the algorithm that correspond to eachhealth degree influencing factor and that are received by the receivingsubmodule.

In a possible implementation, the receiving submodule is specificallyconfigured to receive the at least one health degree influencing factorthat is set by the user and the running parameter and the failure rateparameter that correspond to each health degree influencing factor.

In a possible implementation, the receiving submodule is furtherconfigured to: before the health degree indication information of theto-be-evaluated memory is generated based on the health degree of theto-be-evaluated memory, receive the first preset value range, the secondpreset value range, and the third preset value range that are set by theuser.

In a possible implementation, the receiving submodule is furtherconfigured to: after the matching module separately matches the runningparameter value corresponding to each health degree influencing factorto the health degree evaluation model, to obtain the health degree ofthe to-be-evaluated memory, receive template data that is of theto-be-evaluated memory and that is updated by the user, where thetemplate data includes at least one or more of the following: the atleast one health degree influencing factor, the running parametercorresponding to each of the at least one health degree influencingfactor, the weight corresponding to each health degree influencingfactor, the algorithm corresponding to each health degree influencingfactor, the first preset value range, the second preset value range, andthe third preset value range. The determining submodule is furtherconfigured to update the health degree evaluation model based on theupdated template data that is of the to-be-evaluated memory and that isobtained by the receiving submodule.

According to a third aspect, this application provides a memoryevaluation apparatus. The apparatus includes a processor, a hard disk,at least one memory, a communications interface, an input device, adisplay, and a bus. The hard disk and the at least one memory areconfigured to store at least one instruction. The processor, the harddisk, the at least one memory, the communications interface, the inputdevice, and the display are connected by using the bus. When the memoryevaluation apparatus runs, the processor executes the at least oneinstruction stored in the hard disk and the at least one memory, so thatthe memory evaluation apparatus performs the memory evaluation methodaccording to any one of the first aspect or the implementations of thefirst aspect.

According to a fourth aspect, this application provides a computerstorage medium. The computer storage medium includes at least oneinstruction, and when the at least one instruction is run on a computer,the computer is enabled to perform the memory evaluation methodaccording to any one of the first aspect or the implementations of thefirst aspect.

According to a fifth aspect, this application provides a computerprogram product. The computer program product includes at least oneinstruction, and when the at least one instruction is run on a computer,the computer is enabled to perform the memory evaluation methodaccording to any one of the first aspect or the implementations of thefirst aspect.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a schematic diagram of a hardware structure of a serveraccording to an embodiment of the present application;

FIG. 2 is a schematic architectural diagram of a memory evaluationapparatus according to an embodiment of the present application;

FIG. 2a is another schematic structural diagram of a memory evaluationapparatus according to an embodiment of the present application;

FIG. 3 is a schematic diagram of an MC interface according to anembodiment of the present application;

FIG. 4 is a schematic flowchart of a memory evaluation method accordingto an embodiment of the present application;

FIG. 5 is a schematic diagram of another MC interface according to anembodiment of the present application;

FIG. 6 is a schematic diagram of another MC interface according to anembodiment of the present application;

FIG. 7 is a schematic diagram of another MC interface according to anembodiment of the present application;

FIG. 8-1 and FIG. 8-2 are a schematic diagram of another MC interfaceaccording to an embodiment of the present application;

FIG. 9-1 and FIG. 9-2 are a schematic diagram of another MC interfaceaccording to an embodiment of the present application;

FIG. 10 is a schematic diagram of another MC interface according to anembodiment of the present application;

FIG. 11 is a schematic diagram of another MC interface according to anembodiment of the present application;

FIG. 12 is a schematic diagram of another MC interface according to anembodiment of the present application;

FIG. 13 is a schematic diagram of another MC interface according to anembodiment of the present application;

FIG. 14 is another schematic flowchart of a memory evaluation methodaccording to an embodiment of the present application;

FIG. 15 is a schematic diagram of another MC interface according to anembodiment of the present application;

FIG. 16 is another schematic flowchart of a memory evaluation methodaccording to an embodiment of the present application;

FIG. 17 is a schematic diagram of another MC interface according to anembodiment of the present application;

FIG. 18 is a schematic diagram of another MC interface according to anembodiment of the present application;

FIG. 19 is a schematic diagram of another MC interface according to anembodiment of the present application;

FIG. 20 is a schematic diagram of another MC interface according to anembodiment of the present application;

FIG. 21 is another schematic flowchart of a memory evaluation methodaccording to an embodiment of the present application;

FIG. 22 is a schematic diagram of another MC interface according to anembodiment of the present application;

FIG. 23 is a schematic diagram of another MC interface according to anembodiment of the present application;

FIG. 24 is a schematic diagram of another MC interface according to anembodiment of the present application;

FIG. 25 is a schematic diagram of another MC interface according to anembodiment of the present application;

FIG. 26 is another schematic flowchart of a memory evaluation methodaccording to an embodiment of the present application;

FIG. 27 is a schematic diagram of another MC interface according to anembodiment of the present application;

FIG. 28 is a schematic diagram of another MC interface according to anembodiment of the present application;

FIG. 29 is another schematic flowchart of a memory evaluation methodaccording to an embodiment of the present application;

FIG. 30 is a schematic diagram of another MC interface according to anembodiment of the present application;

FIG. 31 is a schematic diagram of another MC interface according to anembodiment of the present application;

FIG. 32 is another schematic flowchart of a memory evaluation methodaccording to an embodiment of the present application;

FIG. 33 is another schematic structural diagram of a memory evaluationapparatus according to an embodiment of the present application; and

FIG. 34 is another schematic structural diagram of a memory evaluationapparatus according to an embodiment of the present application.

DESCRIPTION OF EMBODIMENTS

Embodiments of the present application provide a memory evaluationmethod and apparatus, to evaluate a health degree of a memory in aserver, and to prompt a user to replace the memory when the memory isnot faulty and has a relatively low health degree, so that the memorycan support normal running of the server.

It should be noted that the memory evaluation method provided in theembodiments of the present application is applied to a server, where theserver is a device configured to provide a computing service. Forexample, the server provided in the embodiments of the presentapplication may be an x86 server, and the x86 server is a server thatuses a complex instruction set computer (CISC) architecture. Certainly,the server provided in the embodiments of the present application mayalternatively be a non-x86 server. This is not limited in solutionsprovided in this application. In the embodiments of the presentapplication, the following uses only the x86 server as an example todescribe the memory evaluation method provided in the embodiments of thepresent application.

A server such as the x86 server includes a hardware system and asoftware system. The hardware system may include components such as aprocessor, a communications interface, a system bus, a hard disk, and amemory. The software system may include an operating system and amanagement system. The management system may be implemented bymanagement software, for example, a management controller (MC). Itshould be noted that the MC in the server may be configured to monitorand manage running data and inherent parameters of components in theserver, for example, running data of a memory in the server and aninherent parameter of the memory. The running data of the memory mayinclude data such as a running temperature and running duration of thememory. It should be noted that, in the following embodiments of thepresent application, “running data of a memory” may be referred to as “arunning parameter value of a memory” or “a running parameter of amemory”. Different names are merely used for ease of description, and donot limit the running data of the memory.

In addition, the inherent parameter of the memory may include a vendorof the memory, a capacity of the memory, a dominant frequency of thememory, a serial number of the memory, a minimum voltage of the memory,a quantity of ranks of the memory, a bit width of the memory, atechnology used for the memory, and the like. For example, the capacityof the memory may be 32768 megabytes (MB). The dominant frequency may be2400 MHz (MHz). The serial number is used to uniquely identify onememory, for example, the serial number is 0x27EACEEA. The minimumvoltage may be 1200 millivolts (mV). The quantity of ranks may be onerank (rank), two ranks, or the like. The bit width may be 64 bits (bit),72 bits, or the like. The used technology may be “Synchronous Registered(Buffered)”.

The health degree of the memory provided in the embodiments of thepresent application can reflect a possibility of a memory failure. Ahigher health degree of the memory indicates a lower possibility of amemory failure (that is, a lower memory failure rate), and usuallyindicates that the memory can run normally and does not need to bereplaced. A lower health degree of the memory indicates a higherpossibility of a memory failure (that is, a higher memory failure rate),and usually indicates that the memory cannot run normally and needs tobe replaced. According to the memory evaluation method provided in theembodiments of the present application, whether to replace the memorymay be determined based on the health degree of the memory before thememory is faulty.

The following describes the technical solutions in the embodiments ofthe present application in detail with reference to the accompanyingdrawings in the embodiments of the present application.

For example, FIG. 1 is a schematic diagram of a hardware structure of aserver according to an embodiment of the present application. The server11 shown in FIG. 1 may include a processor 111, a hard disk 112, atleast one memory 113, a communications interface 114, and a bus 115.

Specifically, the following specifically describes constituent parts ofthe server with reference to FIG. 1.

The processor 111 is a control center of the server, and may be oneprocessor or may be a collective term of a plurality of processingelements. For example, the processor 111 may be a central processingunit (CPU), or an application-specific integrated circuit (ASIC), or maybe configured as one or more integrated circuits implementing thisembodiment of the present application, for example, one or moremicroprocessors (DSP) or one or more field programmable gate arrays(FPGA). For example, the processor 111 may monitor running data of thememory in the server 11 by using an MC.

In specific implementation, in an embodiment, the processor 111 mayinclude one or more CPUs, for example, a CPU 0 and a CPU 1 shown inFIG. 1. Certainly, in specific implementation, in an embodiment, theserver may include a plurality of processors. Each of the processors maybe a single-core (single-CPU) processor, or may be a multi-core(multi-CPU) processor. The processor herein may be one or more devices,circuits, and/or processing cores configured to process data (forexample, a computer program instruction).

The hard disk 112 is an external storage of the server, also referred toas an external storage, and is configured to store a large amount ofpermanent data. Even if the server is powered off, the data is not lost.For example, the hard disk 112 may store a system log in a process inwhich the running data of the memory is monitored by using the MC.Specifically, the hard disk may be implemented by a read-only memory(ROM). In specific implementation, in an embodiment, the hard disk maybe a solid-state drive (SSD), a hard disk drive (HDD), or the like.

Certainly, in addition to the hard disk, the external storage of theserver may alternatively be a compact disc read-only memory (CD-ROM) oranother compact disc storage, or an optical disc storage (including acompact disc, a laser disc, an optical disc, a digital versatile disc, aBlu-ray disc, and the like). This is not described in detail in thisembodiment of the present application.

In this embodiment of the present application, only one of the at leastone memory 113 is used as an example to describe the memory.

The memory 113 is an internal memory that directly exchanges data withthe processor, and is also referred to as a main memory. The memory 113is mainly implemented by a random access memory (RAM) that is alsoreferred to as a random access memory. The memory 113 is configured totemporarily store operational data in the processor and data exchangedwith an external storage such as the hard disk, and all programs in theserver are run in the memory. Specifically, the processor 111 mayperform functions of the server by running or executing software or aprogram stored in the at least one memory 113 and by invoking datastored in the hard disk 112 and/or the at least one memory 113. Forexample, the memory 113 may store a program that is used by theprocessor 111 to monitor the running data of the memory in the server11.

In specific implementation, in an embodiment, the memory 113 may be aRAM such as a static random access memory SRAM) or a dynamic randomaccess memory DRAM). The memory provided in this embodiment of thepresent application may be a swappable memory module in the server. Inspecific implementation, in an embodiment, the memory 113 may beimplemented by a dual in-line memory module (DIMM), or a double datarate synchronous dynamic random access memory (DDR SDRAM) that is alsoreferred to as DDR.

It should be noted that the inherent parameter of the memory may furtherinclude a memory type. For example, memory types may include types suchas DDR, DDR2, DDR3, and DDR4. In addition, each memory in the server mayfurther have a name, for example, DIMM000, DIMM011, or the like.

The communications interface 114 may be configured to interact with anexternal device. For example, the communications interface 114 mayinclude two communications interfaces: a sending interface configured tosend data to the external device and a receiving interface configured toreceive data from the external device. To be specific, a sending devicemay respectively receive and send data through the two differentcommunications interfaces. For example, the data stored in the hard disk112 and the at least one memory 113 may be sent through onecommunications interface of the server 11 to the external device.Certainly, the communications interface 114 may integrate a datareceiving function and a data sending function into one communicationsinterface, and the communications interface has both the data receivingfunction and the data sending function. For example, the communicationsinterface 114 may be an MC interface.

The processor 111, the hard disk 112, the at least one memory 113, andthe communications interface 114 may be connected by using the bus 115.The bus 115 may be a peripheral component interconnect (PCI) bus, anextended industry standard architecture (EISA) bus, or the like. The bus115 may be classified into an address bus, a data bus, a control bus,and the like. For ease of representation, only one thick line is used torepresent the bus in FIG. 1, but this does not mean that there is onlyone bus or only one type of bus.

For example, with reference to the server 11 shown in FIG. 2, one memory113 may be installed below each CPU in the processor 111 in the server11.

The hardware structure of the server shown in FIG. 1 does not constitutea limitation on the server. The server may include more or fewercomponents than those shown in the figure, or combine some components,or have a different component arrangement. For example, the server 11further includes components such as one or more temperature sensors. Theone or more temperature sensors may be configured to detect temperaturesof some components in the server, for example, a temperature of a CPUand a temperature of each memory.

It should be noted that, while the running data of the at least onememory 113 is being detected by using the MC in the server 11, the MCmay be managed in a human-computer interaction manner, so that a usercan intuitively observe or manage the data obtained by the MC, forexample, the running data and the inherent parameter of the at least onememory 113. Specifically, an input device and a display may be connectedto the server 11, to implement human-computer interaction.

For example, FIG. 2 is a schematic architectural diagram of a memoryevaluation apparatus according to an embodiment of the presentapplication. The memory evaluation apparatus 20 shown in FIG. 2 includesa server 11, an input device 12, and a display 13. In FIG. 2, only astraight line is used to represent a connection relationship between theserver 11, the input device 12, and the display 13. A connection betweenthe server 11, the input device 12, and the display 13 may be a wiredconnection or a wireless connection. This is not limited in thisembodiment of the present application.

Optionally, the input device 12 and the display 13 may be provided witha service by the server 11, and a service in the server 11 may beimplemented by the processor 11 in combination with the input device 12and the display 13. The memory evaluation apparatus 10 may beimplemented by a terminal device such as a desktop computer alsoreferred to as a desktop computer or a desktop computer (desktopcomputer). In this case, the server 11 is referred to as a host, and theinput device 12 may be an apparatus such as a keyboard or a mouse. Forexample, the memory evaluation apparatus 10 including the server 11, theinput device 12, and the display 13 may belong to a same desktopcomputer that is denoted as a terminal device 1.

Optionally, the input device 12 and the display 13 are not provided witha service by the server 11, but are provided with a service by anotherserver. For example, the server 11 provides a service for the terminaldevice 1, whereas the input device 12 and the display 13 belong to aterminal device 2. The terminal device 2 may be another desktopcomputer.

In addition, in specific implementation, in an embodiment, the terminaldevice 2 may be a terminal device that has a touchscreen. The terminaldevice may be a terminal device such as a mobile phone, a tabletcomputer, a notebook computer, an ultra-mobile personal computer (UMPC),a netbook, or a personal digital assistant (PDA). In this case, theinput device 12 and the display 13 may be implemented by the touchscreenof the terminal device 2.

A specific composition manner of the server 11, the input device 12, andthe display 13 that are included in the memory evaluation apparatusprovided in this embodiment of the present application is not limited.The following describes the memory evaluation method provided in theembodiments of the present application by using only an example in whichthe server 11, the input device 12, and the display 13 that are includedin the memory evaluation apparatus provided in this embodiment of thepresent application are provided by a same terminal device.

Specifically, with reference to the memory evaluation apparatus 20 shownin FIG. 2 and the server 11 shown in FIG. 1, FIG. 2a is anotherschematic structural diagram of a memory evaluation apparatus accordingto an embodiment of the present application. In FIG. 2 a, the memoryevaluation apparatus 20 includes a processor 111, a hard disk 112, atleast one memory 113, a communications interface 114, a bus 115, aninput device 12, and a display 13.

It should be noted that, according to the memory evaluation methodprovided in the embodiments of the present application, a human-computerinteraction interface of an MC may be displayed by using the display 13,and the human-computer interaction interface of the MC may be a DOSinterface or a browser interface. In the embodiments of the presentapplication, the following describes the memory evaluation methodprovided in the embodiments of the present application by using only anexample in which the human-computer interaction interface of the MC isthe browser interface. One MC may correspond to one login address, forexample, a uniform resource locator (URL). In this case, the inputdevice 12 may receive the login address that is of the MC and that isentered by a user, and the display 13 may display the human-computerinteraction interface (hereinafter referred to as an MC interface) ofthe MC by using the browser interface. In the embodiments of the presentapplication, the following describes the memory evaluation methodprovided in the embodiments of the present application by using only anexample in which the display displays the MC interface after the useralready enters the login address of the MC by using the input device.

Specifically, the MC interface displayed on the display may be agraphical user interface (GUI). In addition, the GUI includes a graphicoption in a text form and a graphic option in an icon form. In the GUI,both the graphic option in the text form and the graphic option in theicon form may be operated by the user by using a mouse, a keyboard, atouchscreen, or another input device.

The GUI includes a window, a drop-down list, a dialog box, and acorresponding control mechanism (for example, a CPU of the server) ofthe GUI. In addition, the GUI is standardized in various types of newapplication programs or new software, to be specific, a same operationis always completed in a same manner. For example, a tap/click operationperformed on any graphic option (hereinafter referred to as an option)in a text form or an icon form in the GUI may be clicking the option bythe user by using the mouse, or tapping the option on the touchscreen bythe user by using a finger. After the user performs a tap/clickoperation on one option, the processor may generate a correspondingtap/click operation instruction, and respond to the tap/click operation.

For example, FIG. 3 is a schematic diagram of an MC interface accordingto an embodiment of the present application. The MC interface in FIG. 3separately shows inherent parameters of six memories named DIMM000,DIMM001, DIMM002, DIMM010, DIMM011, and DIMM012. The MC interface shownin FIG. 3 includes options such as “name ▾”, “vendor ▾”, “capacity ▾”,“dominant frequency ▾”, and “serial number ▾”. “▾” included in eachoption corresponds to one drop-down list. For example, a user mayperform a tap/click operation on an option 31 by using an input device,that is, a “▾” option in the “vendor ▾” option. After generating acorresponding tap/click operation instruction, a processor in a memoryevaluation apparatus instructs a display to display a drop-down list 311corresponding to “vendor ▾” shown in FIG. 3, where the drop-down list311 includes three options: “vendor A”, “vendor B”, and “vendor C”. Ifthe user performs a tap/click operation on “vendor A” in the drop-downlist 311, the processor in the memory evaluation apparatus may generatea corresponding tap/click operation instruction, and instruct thedisplay to display, in the MC interface shown in FIG. 3, only aninherent parameter of a memory whose vendor is the vendor A.

To make the objectives, technical solutions, and advantages of theembodiments of the present application clearer, the following describesin detail the memory evaluation method provided in the embodiments ofthe present application, with reference to specific components in thememory evaluation apparatus shown in FIG. 2a and by using a flowchart ofa memory evaluation method shown in FIG. 4. In addition, although alogical sequence of the memory evaluation method provided in thisembodiment of the present application is shown in the method flowchart,in some cases, the shown or described steps may be performed in asequence different from the sequence herein.

S401: A memory evaluation apparatus determines a health degreeevaluation model of a to-be-evaluated memory.

For example, step 401 may be performed by the processor 111 in thememory evaluation apparatus 20 shown in FIG. 2 a.

The to-be-evaluated memory is one of at least one memory in a server,that is, one memory in the memory evaluation apparatus. The healthdegree evaluation model of the to-be-evaluated memory is used toevaluate a health degree of the to-be-evaluated memory, and the healthdegree of the to-be-evaluated memory can reflect a possibility of afailure of the to-be-evaluated memory, that is, a memory failure rate ofthe to-be-evaluated memory.

Specifically, the health degree evaluation model is a relationship inwhich the health degree of the to-be-evaluated memory changes with atleast one health degree influencing factor of the to-be-evaluatedmemory, one health degree influencing factor corresponds to one runningparameter and one failure rate parameter, and one health degreeinfluencing factor corresponds to one weight, where the weight is aconstant. For one health degree influencing factor, a value of a failurerate parameter of the memory (that is, a memory failure rate) changeswith a value of a corresponding running parameter (that is, runningdata).

It should be noted that a health degree influencing factor correspondingto one memory may affect normal running of the memory, and may cause afailure of the memory, that is, cause the memory to fail. For one healthdegree influencing factor corresponding to one memory (for example, theto-be-evaluated memory), the memory evaluation apparatus stores datathat describes a relationship between a corresponding running parameterand a corresponding failure rate parameter, for example, a curve thatdescribes the relationship between the failure rate parameter and therunning parameter.

For one health degree influencing factor of the to-be-evaluated memory,data that is stored in the memory evaluation apparatus and thatdescribes a relationship between a corresponding running parameter and acorresponding failure rate parameter may be obtained by a person skilledin the art through training based on a large amount of data (forexample, a large amount of running data of a memory related to theto-be-evaluated memory), or may be obtained based on related documentsin the art. Details are not described in this embodiment of the presentapplication.

In addition, the weight corresponding to one health degree influencingfactor can indicate an extent to which the health degree influencingfactor affects the health degree of the to-be-evaluated memory, andhealth degree influencing factors corresponding to different weightshave different impact on the health degree of the to-be-evaluatedmemory. For example, a larger weight corresponding to a health degreeinfluencing factor indicates greater impact of the health degreeinfluencing factor on the health degree of the to-be-evaluated memory.In this way, a weight corresponding to each health degree influencingfactor in the health degree evaluation model provided in this embodimentof the present application can indicate impact of each health degreeinfluencing factor on the health degree of the to-be-evaluated memory,so that impact extents of different health degree evaluation factors forthe to-be-evaluated memory in the health degree evaluation model aremore proper for the to-be-evaluated memory. This helps to accuratelyevaluate the health degree of the to-be-evaluated memory.

The weight corresponding to each health degree influencing factor in thehealth degree evaluation model of the to-be-evaluated memory may bepreset by a person skilled in the art. Certainly, the weightcorresponding to each health degree influencing factor may alternativelybe independently set by a user based on experience or related statisticsof the to-be-evaluated memory. Usually, a person skilled in the art mayset different weights for all health degree influencing factors in thehealth degree evaluation model of the to-be-evaluated memory. Forexample, the to-be-evaluated memory corresponds to two health degreeinfluencing factors, a weight corresponding to one of the two healthdegree influencing factors is 60%, and a weight corresponding to theother health degree influencing factor is 40%. A sum of the weightscorresponding to all of the at least one health degree influencingfactor is equal to 1.

Optionally, a person skilled in the art may set a same weight for allhealth degree influencing factors in the health degree evaluation modelof the to-be-evaluated memory, or a person skilled in the art may notset a weight for any health degree influencing factor. In other words,all the health degree influencing factors have same impact on the healthdegree of the to-be-evaluated memory.

S402: The memory evaluation apparatus obtains at least one runningparameter value corresponding to each of the at least one health degreeinfluencing factor.

For example, step 402 may be performed by the processor 111 in thememory evaluation apparatus 20 shown in FIG. 2 a.

For one health degree influencing factor corresponding to theto-be-evaluated memory, a running parameter included in the healthdegree evaluation model corresponds to at least one running parametervalue. Therefore, for the one health degree influencing factorcorresponding to the to-be-evaluated memory, the memory evaluationapparatus may obtain the at least one running parameter value based onthe corresponding running parameter. For example, for theto-be-evaluated memory, the memory evaluation apparatus may obtain totalrunning duration, of the to-be-evaluated memory, corresponding to ahealth degree influencing factor that is total memory running duration.

It may be figured out that before the processor in the memory evaluationapparatus obtains the total running duration of the to-be-evaluatedmemory, the total running duration of the to-be-evaluated memory may bestored in a hard disk of the memory evaluation apparatus, and may beupdated by the processor in the memory evaluation apparatus.

S403: The memory evaluation apparatus separately matches the at leastone running parameter value corresponding to each health degreeinfluencing factor to the health degree evaluation model, to obtain thehealth degree of the to-be-evaluated memory.

It should be noted that, when the health degree evaluation model is therelationship in which the health degree of the to-be-evaluated memorychanges with the at least one health degree influencing factor of theto-be-evaluated memory, the memory evaluation apparatus may match, withthe corresponding running parameter in the health degree evaluationmodel, the at least one running parameter value that corresponds to thehealth degree influencing factor and that is obtained by a memoryevaluation model. In this way, the memory evaluation apparatus canobtain the health degree of the to-be-evaluated memory by using thehealth degree evaluation model of the to-be-evaluated memory.

For example, the health degree of the to-be-evaluated memory may berepresented by a value in a range from 0 to 100, for example, 80. Alarger value of the health degree of the to-be-evaluated memoryindicates a higher health degree of the to-be-evaluated memory. Asmaller value of the health degree of the to-be-evaluated memoryindicates a lower health degree of the to-be-evaluated memory.

S404: The memory evaluation apparatus outputs health degree indicationinformation of the to-be-evaluated memory based on the health degree ofthe to-be-evaluated memory.

For example, in step 402, the processor 111 in the memory evaluationapparatus 20 shown in FIG. 2a may generate the health degree indicationinformation of the to-be-evaluated memory, and instruct the display 13in the memory evaluation apparatus 20 to output the health degreeindication information of the to-be-evaluated memory.

The health degree indication information of the to-be-evaluated memoryis used to indicate, to the user, whether to replace the to-be-evaluatedmemory. For example, when the health degree of the to-be-evaluatedmemory is relatively low, the health degree indication information thatis of the to-be-evaluated memory and that is output by the memoryevaluation apparatus may indicate, to the user, that the to-be-evaluatedmemory needs to be replaced. In this case, there is a relatively highpossibility of a failure of the to-be-evaluated memory. When the healthdegree of the to-be-evaluated memory is relatively high, the healthdegree indication information that is of the to-be-evaluated memory andthat is output by the memory evaluation apparatus may indicate, to theuser, that the to-be-evaluated memory does not need to be replaced. Inthis case, there is a relatively low possibility of a failure of theto-be-evaluated memory.

For example, when the value of the health degree of the to-be-evaluatedmemory is within a preset value range (for example, from 70 to 100), thememory evaluation apparatus outputs the health degree indicationinformation of the to-be-evaluated memory to indicate, to the user, thatthe to-be-evaluated memory does not need to be replaced. When the valueof the health degree of the to-be-evaluated memory is within a presetvalue range (for example, from 0 to 45), the memory evaluation apparatusoutputs the health degree indication information of the to-be-evaluatedmemory to indicate, to the user, that the to-be-evaluated memory needsto be replaced.

It should be noted that the health degree evaluation model of theto-be-evaluated memory may be pre-stored by a person skilled in the artin the memory evaluation apparatus, for example, in the hard disk 112 inthe memory evaluation apparatus 20 shown in FIG. 2 a. In addition, in aprocess in which the memory evaluation apparatus executes the memoryevaluation method provided in this embodiment of the presentapplication, a log may be generated. The log may store data in thehealth degree evaluation model of the to-be-evaluated memory (forexample, the at least one health degree influencing factor of theto-be-evaluated memory) and the health degree of the to-be-evaluatedmemory.

It should be noted that this embodiment of the present application canprovide the health degree evaluation model that describes therelationship in which the health degree of the to-be-evaluated memorychanges with the at least one health degree influencing factor of theto-be-evaluated memory, so that the memory evaluation apparatus canobtain the health degree of the to-be-evaluated memory based on thehealth degree evaluation model of the to-be-evaluated memory. Therefore,the memory evaluation apparatus can generate the health degreeindication information of the to-be-evaluated memory based on the valueof the health degree of the to-be-evaluated memory. In this way, beforethe to-be-evaluated memory is faulty, the memory evaluation apparatuscan determine, based on the health degree of the to-be-evaluated memory,whether to replace the to-be-evaluated memory. In addition, the memoryevaluation apparatus can output the health degree indication informationof the to-be-evaluated memory when the memory is not faulty and thehealth degree of the memory is relatively low, to prompt the user toreplace the memory, so that the memory can support normal running of theserver.

In a specific embodiment, in addition to the total running duration ofthe to-be-evaluated memory, the at least one health degree influencingfactor included in the health degree evaluation model provided in thisembodiment of the present application may further include another healthdegree influencing factor.

Specifically, the at least one health degree influencing factor providedin this embodiment of the present application includes one or more ofthe following:

a factor 1: a memory running temperature factor;

a factor 2: a memory service load factor;

a factor 3: a total memory running duration factor;

a factor 4: a memory swap factor;

a factor 5: a memory correctable error (CE) frequency factor;

a factor 6: a memory UCE frequency factor; and

a factor 7: a memory performance attenuation factor.

It should be noted that the health degree influencing factors providedin this embodiment of the present application may be obtained by aperson skilled in the art through training based on a large amount ofdata (for example, running data of the memory), or may be obtained basedon related documents in the art. Details are not described in thisembodiment of the present application.

Certainly, the health degree influencing factor provided in thisembodiment of the present application is not limited to the foregoinglisted health degree influencing factors (the factors 1 to 7), and mayalternatively be another factor, for example, sulfidation intensity inair.

It should be noted that the MC interface provided in this embodiment ofthe present application may display the health degree evaluation modelof the memory in addition to inherent parameters of memories.

For example, FIG. 5 shows another MC interface according to anembodiment of the present application, and the MC interface is aninterface used for setting health degree evaluation models for differentto-be-evaluated memories. The MC interface shown in FIG. 5 may be aninterface provided for a desktop computer. In this case, the displayprovided in this embodiment of the present application may be a displayof the desktop computer, and the input device may be a device such as amouse or a keyboard of the desktop computer.

The MC interface 50 shown in FIG. 5 includes a “memory name” option 51,and the option 51 includes a “▾” option. The MC interface 50 includesseven health degree influencing factor options: a “memory runningtemperature” option, a “memory service load” option, a “total memoryrunning duration” option, a “memory swap” option, a “memory CEfrequency” option, a “memory UCE frequency” option, and a “memoryperformance attenuation” option. Each health degree influencing factorcorresponds to one “close” option. For example, a factor 1 correspondsto the “memory running temperature” option 52, and the factor 1corresponds to a “close” option 53. In addition, the MC interface 50shown in FIG. 5 further includes a “determine” option 54 and a “cancel”option 55.

Specifically, the MC interface 50 may provide a user with choices ofdifferent memory names, so that the user sets health degree influencingfactors included in health degree evaluation models for differentmemories. For example, the user performs a tap/click operation on a “▾”option included in the option 51 in the MC interface 50, so that aftergenerating a corresponding tap/click operation instruction, a processorin a memory evaluation apparatus instructs the display to display, inthe MC interface, a drop-down list 511 that is shown in FIG. 6. Thedrop-down list 511 includes six options: a “DIMM000” option, a “DIMM001”option, a “DIMM002” option, a “DIMM010” option, a “DIMM011” option, anda “DIMM012” option. The user performs a tap/click operation on anyoption (for example, the “DIMM000” option) included in the drop-downlist 511, so that after receiving a corresponding operation instruction,the processor in the memory evaluation apparatus indicates that a healthdegree influencing factor option displayed in the MC interface 50 is ahealth degree influencing factor corresponding to a memory whose memoryname is DIMM000. In this case, the memory whose memory name is DIMM000is a to-be-evaluated memory. It may be figured out that after the userperforms a tap/click operation on the “DIMM000” option included in thedrop-down list 511 shown in FIG. 6, the processor in the memoryevaluation apparatus may generate a corresponding tap/click operationinstruction, and then may instruct the display to display the MCinterface 50 shown in FIG. 5. The health degree influencing factoroption displayed in the MC interface 50 in FIG. 5 is the health degreeinfluencing factor corresponding to the memory whose memory name isDIMM000. That “the user performs a tap/click operation on the option”may be that the user clicks the option by using the mouse. An arrowshown in FIG. 5 is used to indicate a location of a cursor of the mouseon the display interface.

After the user performs a tap/click operation (one tap/click operation)on a “close” option corresponding to one health degree influencingfactor option in the MC interface 50, the memory evaluation apparatusmay determine that a corresponding health degree evaluation model doesnot include the health degree influencing factor, that is, ignore impactof the health degree influencing factor on a health degree of theto-be-evaluated memory. If the user does not perform a tap/clickoperation (or consecutively performs two tap/click operations) on the“close” option corresponding to the health degree influencing factor,the memory evaluation apparatus may determine that the health degreeinfluencing factor in the corresponding health degree evaluation modelhas impact on the health degree of the to-be-evaluated memory. In theembodiments of the present application, the following describes thememory evaluation method provided in the embodiments of the presentapplication, by using only an example in which one tap/click operationis performed on each option in the MC interface 50.

For example, a tap/click operation may be performed on a “close” option53 corresponding to a factor 1 included in an MC interface 50 shown inFIG. 7. In this case, it may be considered that a health degree of amemory whose memory name is “DIMM000” is not affected by a health degreeinfluencing factor that is a memory running temperature. To be specific,a user may select a health degree influencing factor of a memory byperforming a tap/click operation on a related option in the MC interface50.

It should be noted that, after selecting, in the MC interface 50, thehealth degree influencing factor of the memory whose memory name is“DIMM000”, the user may perform a tap/click operation on a “determine”option 54, so that a processor in a memory evaluation apparatusdetermines a health degree evaluation model of the to-be-evaluatedmemory. Alternatively, the user may perform a tap/click operation on the“cancel” option 55, so that the processor re-determines a health degreeevaluation model of the to-be-evaluated memory.

In addition, a display for displaying the MC interface provided in thisembodiment of the present application may be implemented by a terminaldevice having a touchscreen, such as a mobile phone or a tabletcomputer.

For example, FIG. 8-1 and FIG. 8-2 shows another MC interface accordingto an embodiment of the present application. The MC interface isimplemented by a touchscreen of a mobile phone. Each of the MCinterfaces 80 shown in FIG. 8-1 and FIG. 8-2 includes a memory nameoption 81, and the option 81 includes a “▾” option. The MC interface 80includes seven health degree influencing factor options: a “memoryrunning temperature” option, a “memory service load” option, a “totalmemory running duration” option, a “memory swap” option, a “memory CEfrequency” option, a “memory UCE frequency” option, and a “memoryperformance attenuation” option. Each health degree influencing factoroption corresponds to one “close” option. For example, a health degreeinfluencing factor option corresponding to a factor 1 is a “memoryrunning temperature” option 82, and the factor 1 corresponds to a“close” option 83. In addition, the MC interface 80 further includes a“determine” option 84 and a “cancel” option 85. A drop-down list 811shown in FIG. 8-2 includes six options: a “DIMM000” option, a “DIMM001”option, a “DIMM002” option, a “DIMM010” option, a “DIMM011” option, anda “DIMM012” option.

For example, FIG. 9-1 and FIG. 9-2 shows another MC interface accordingto an embodiment of the present application. The MC interface isimplemented by a touchscreen of a tablet computer. Each of the MCinterfaces 90 shown in FIG. 9-1 and FIG. 9-2 includes a memory nameoption 91, and the option 91 includes a “▾” option. The MC interface 90includes seven health degree influencing factor options: a “memoryrunning temperature” option, a “memory service load” option, a “totalmemory running duration” option, a “memory swap” option, a “memory CEfrequency” option, a “memory UCE frequency” option, and a “memoryperformance attenuation” option. Each health degree influencing factoroption corresponds to one “close” option. For example, a health degreeinfluencing factor option corresponding to a factor 1 is a “memoryrunning temperature” option 92, and the factor 1 corresponds to a“close” option 93. In addition, the MC interface 90 further includes a“determine” option 94 and a “cancel” option 95. A drop-down list 911shown in FIG. 9-2 includes six options: a “DIMM000” option, a “DIMM001”option, a “DIMM002” option, a “DIMM010” option, a “DIMM011” option, anda “DIMM012” option.

A user may perform a tap operation by using a finger on the MC interfacepresented on the touchscreen shown in FIG. 8-1, FIG. 8-2 or FIG. 9-1,FIG. 9-2, and then a processor in the mobile phone or the tabletcomputer may generate a corresponding tap operation instruction. A “handicon” in FIG. 8-1, FIG. 8-2 and FIG. 9-1, FIG. 9-2 is used toschematically represent a hand. In this embodiment of the presentapplication, the “hand icon” is merely used to represent a location ofthe finger of the user. In actuality, the “hand icon” is not displayedon the mobile phone or the tablet computer.

It should be noted that, for specific descriptions of the MC interfaceprovided by the terminal device having the touchscreen, such as themobile phone or the tablet computer, reference may be made todescriptions of the MC interface provided by the display of the desktopcomputer in the embodiment of the present application. Details are notdescribed in this embodiment of the present application. In theembodiments of the present application, the following describes thememory evaluation method provided in the embodiments of the presentapplication, by using only the MC interface provided by the display ofthe desktop computer as an example.

It may be figured out that health degrees of memories of different lotsor different models (to be specific, with different inherent parameters)may be related to different health degree influencing factors. Forexample, health degrees of some memories are more sensitive to a changeof a memory running temperature, and health degrees of some memories aremore sensitive to a change of memory running duration. In this case, aplurality of health degree influencing factors are preset in a healthdegree evaluation model provided in this embodiment of the presentapplication, so that the user can select corresponding health degreeinfluencing factors for different to-be-evaluated memories. In this way,a health degree evaluation factor for a to-be-evaluated memory in thehealth degree evaluation model is more proper for the to-be-evaluatedmemory. This helps to accurately evaluate a health degree of theto-be-evaluated memory.

Optionally, a person skilled in the art may set a same weight for allthe health degree influencing factors in the health degree evaluationmodel of the to-be-evaluated memory, or a person skilled in the art maynot set a weight for any health degree influencing factor. In otherwords, all the health degree influencing factors have same impact on thehealth degree of the to-be-evaluated memory.

For example, a weight corresponding to the factor 1 is 20%, a weightcorresponding to a factor 2 is 5%, a weight corresponding to a factor 3is 25%, a weight corresponding to a factor 4 is 5%, a weightcorresponding to a factor 5 is 10%, a weight corresponding to a factor 6is 15%, and a weight corresponding to a factor 7 is 20%. Each healthdegree influencing factor corresponds to one weight, and the weight mayfurther indicate impact of each health degree influencing factor on thehealth degree of the to-be-evaluated memory.

FIG. 10 is a schematic diagram of another MC interface according to anembodiment of the present application. In the MC interface 50 shown inFIG. 10, each health degree influencing factor corresponds to one weightoption. For example, a factor 1 shown in FIG. 1 corresponds to a “20%”option (that is, an option 56). It may be figured out that a user maychange any weight displayed in the MC interface 50. For example, after atap/click operation is performed on the option 56 shown in FIG. 10, aprocessor (a processor in a server) in a memory evaluation apparatus maygenerate a corresponding tap/click operation instruction, and receive achange that is performed by the user on the option 56 by using an inputdevice (for example, a keyboard), for example, modify “20%” in theoption 56 to “25%”. In this case, in addition to “20%” in the option 56,a weight corresponding to another factor may be correspondinglymodified.

In a specific embodiment, a running parameter corresponding to a memoryrunning temperature factor (the factor 1) provided in this embodiment ofthe present application is a running temperature of a to-be-evaluatedmemory, a running parameter corresponding to the memory service loadfactor (a factor 2) is a quantity of charging/discharging times of theto-be-evaluated memory, a running parameter corresponding to the totalmemory running duration factor (a factor 3) is total running duration ofthe to-be-evaluated memory, a running parameter corresponding to thememory swap factor (a factor 4) is a quantity of swap times of theto-be-evaluated memory, a running parameter corresponding to the memoryCE frequency factor (a factor 5) is a quantity of CEs of theto-be-evaluated memory or a CE frequency of the to-be-evaluated memory,a running parameter corresponding to the memory UCE frequency factor (afactor 6) is a quantity of UCEs of the to-be-evaluated memory or a UCEfrequency of the to-be-evaluated memory, and a running parametercorresponding to the memory performance attenuation factor (a factor 7)is a performance value attenuation magnitude of the to-be-evaluatedmemory.

The running parameters corresponding to the health degree influencingfactors provided in this embodiment of the present application may beobtained by a person skilled in the art through training based on alarge amount of data, for example, obtained through training based onrunning data of a plurality of memories similar to the to-be-evaluatedmemory, or may be obtained based on related documents in the art.Details are not described in this embodiment of the present application.

Specifically, when a health degree influencing factor corresponding tothe to-be-evaluated memory is the factor 1, the memory evaluationapparatus stores data that describes a relationship between the runningtemperature of the to-be-evaluated memory and a failure rate parameter,for example, a curve that describes how a memory failure rate of theto-be-evaluated memory changes with the running temperature of theto-be-evaluated memory. Generally, a higher running temperature of theto-be-evaluated memory indicates a higher possibility of a failure ofthe to-be-evaluated memory, that is, a higher failure rate.

Similarly, when a health degree influencing factor corresponding to theto-be-evaluated memory is the factor 2, the memory evaluation apparatusstores data that describes a relationship between the quantity ofcharging/discharging times of the to-be-evaluated memory and a failurerate parameter, for example, a curve that describes how a memory failurerate of the to-be-evaluated memory changes with the quantity ofcharging/discharging times of the to-be-evaluated memory. During normalworking of one memory (for example, the to-be-evaluated memory), one ormore services, such as a data storage service or a data modificationservice, may be run in the memory. Running of the services in the memoryis accompanied with a service load pressure of the memory. The serviceload pressure of the memory may be represented by the quantity ofcharging/discharging times of the memory. Generally, a larger quantityof charging/discharging times of the memory indicates a higher serviceload pressure of the memory, a higher possibility of a failure of thememory, and a higher failure rate of the memory. A smaller quantity ofcharging/discharging times of the memory indicates a lower service loadpressure of the memory, a lower possibility of a failure of the memory,and a lower failure rate of the memory.

When a health degree influencing factor corresponding to theto-be-evaluated memory is the factor 3, the memory evaluation apparatusstores data that describes a relationship between the total runningduration of the to-be-evaluated memory and a failure rate parameter, forexample, a curve that describes how a memory failure rate of theto-be-evaluated memory changes with the total running duration of theto-be-evaluated memory. Total running duration of one memory (forexample, the to-be-evaluated memory) is limited. In other words, a lifespan of one memory is limited. Generally, longer total running durationof one memory indicates a higher possibility of a failure of the memory,and a higher failure rate.

When a health degree influencing factor corresponding to theto-be-evaluated memory is the factor 4, the memory evaluation apparatusstores data that describes a relationship between the quantity of swaptimes of the to-be-evaluated memory and a failure rate parameter, forexample, a curve that describes how a memory failure rate of theto-be-evaluated memory changes with the quantity of swap times of theto-be-evaluated memory. The memory (for example, the to-be-evaluatedmemory) provided in this embodiment of the present application is mostlya memory module having a gold coating. Because a thickness of the goldcoating of the memory module is fixed, and wear of the gold coating ofthe memory module is caused in a process of swapping the memory module,a quantity of memory swap times may be a health degree influencingfactor of one memory. Specifically, a larger quantity of swap times ofthe to-be-evaluated memory indicates a higher possibility of a failureof the to-be-evaluated memory, and a higher failure rate. A smallerquantity of swap times of the to-be-evaluated memory indicates a lowerpossibility of a failure of the to-be-evaluated memory, and a lowerfailure rate.

When a health degree influencing factor corresponding to theto-be-evaluated memory is the factor 5, the memory evaluation apparatusstores data that describes a relationship between the quantity of CEs ofthe to-be-evaluated memory or the CE frequency of the to-be-evaluatedmemory and a failure rate parameter, for example, a curve that describeshow a memory failure rate of the to-be-evaluated memory changes with thequantity of CEs of the to-be-evaluated memory or the CE frequency of theto-be-evaluated memory. A larger quantity of CEs generated by theto-be-evaluated memory in a period of time indicates a higherpossibility of a failure of the to-be-evaluated memory, and a higherfailure rate. A smaller quantity of CEs generated by the to-be-evaluatedmemory in a period of time indicates a lower possibility of a failure ofthe to-be-evaluated memory, and a lower failure rate. Alternatively, ahigher CE frequency of the to-be-evaluated memory indicates a higherpossibility of a failure of the to-be-evaluated memory, and a higherfailure rate. A lower CE frequency of the to-be-evaluated memoryindicates a lower possibility of a failure of the to-be-evaluatedmemory, and a lower failure rate.

When a health degree influencing factor corresponding to theto-be-evaluated memory is the factor 6, the memory evaluation apparatusstores data that describes a relationship between the quantity of UCEsof the to-be-evaluated memory or the UCE frequency of theto-be-evaluated memory and a failure rate parameter, for example, acurve that describes how a memory failure rate of the to-be-evaluatedmemory changes with the quantity of UCEs of the to-be-evaluated memoryor the UCE frequency of the to-be-evaluated memory. A larger quantity ofUCEs generated by the to-be-evaluated memory in a period of time (or ahigher UCE frequency of the to-be-evaluated memory) indicates a higherpossibility of a failure and a higher failure rate. A smaller quantityof UCEs generated by the to-be-evaluated memory in a period of time (ora lower CE frequency of the to-be-evaluated memory) indicates a lowerpossibility of a failure and a lower failure rate. For example, when thequantity of UCEs of the to-be-evaluated memory is 1 or 2, there is arelatively high possibility of a failure of the to-be-evaluated memory.

When a health degree influencing factor corresponding to theto-be-evaluated memory is the factor 7, the memory evaluation apparatusstores data that describes a relationship between the performance valueattenuation magnitude of the to-be-evaluated memory and a failure rateparameter, for example, a curve that describes how a failure rate of theto-be-evaluated memory changes with the performance value attenuationmagnitude of the to-be-evaluated memory. The performance valueattenuation magnitude of the to-be-evaluated memory changes in a runningprocess of the to-be-evaluated memory. Generally, a larger performancevalue attenuation magnitude and a smaller performance value of onememory (for example, the to-be-evaluated memory) indicate a higherpossibility of a failure and a higher failure rate. A smallerperformance value attenuation magnitude and a larger performance valueof the memory indicate a lower possibility of a failure and a lowerfailure rate.

It should be noted that the MC interface provided in this embodiment ofthe present application may display data of a relationship between arunning parameter and a failure rate parameter that correspond to eachhealth degree influencing factor, for example, a curve that describeshow a value of the failure rate parameter of the memory changes with avalue of the corresponding running parameter. The memory evaluationapparatus stores a curve that describes how failure rates of memories(for example, a memory named “DIMM000” and a memory named “DIMM001”)change with corresponding running parameters.

For example, FIG. 11 is a schematic diagram of another MC interfaceaccording to an embodiment of the present application. Each healthdegree influencing factor in the MC interface 50 shown in FIG. 11corresponds to one “set” option. For example, a “memory runningtemperature” option 52 corresponds to a “set” option 57. Specifically,the “set” option 57 is used to enable an MC interface 50 shown in FIG.12 to jump to an interface 50 displaying a “temperature-failure ratecurve”.

After a tap/click operation is performed on the “set” option 57corresponding to a factor 1 shown in FIG. 11, a processor in a memoryevaluation apparatus may generate a corresponding tap/click operationinstruction, and instruct a display to display the MC interface 50 thatincludes a window 511 and that is shown in FIG. 12, where the window 511displays the “temperature-failure rate curve”. The “temperature-failurerate curve” shown in FIG. 12 is a curve that describes how a value of afailure rate parameter of a memory named “DIMM000” changes with a valueof a running parameter that is a memory running temperature. The MCinterface 50 shown in FIG. 12 further includes a “determine” option 512.The “determine” option 512 is used by a user to determine the“temperature-failure rate curve”, so that the display displays the MCinterface 50 shown in FIG. 11.

For example, referring to the “temperature-failure rate curve” in FIG.12, when the running temperature of the memory named “DIMM000” is 45° C.for a long time, the failure rate of the memory is 40%. When the runningtemperature of the memory named “DIMM000” is 80° C. for a long time, thefailure rate of the memory is 95%. The “long time” may be a time used bya person skilled in the art to detect a life span of one memory, anddetails are not described in this embodiment of the present application.

It should be noted that the “temperature-failure rate” curve is a curvefor the memory named “DIMM000”, and may be obtained by the memoryevaluation apparatus through matching from a plurality of curves fordifferent memories. The plurality of curves for different memories maybe pre-stored in the memory evaluation apparatus. Specifically, thememory evaluation apparatus may autonomously obtain the foregoing“temperature-failure rate” curve through matching based on an inherentparameter such as a memory capacity of the memory named “DIMM000”.

After a tap/click operation is performed on a “set” option correspondingto a factor 2 included in the MC interface shown in FIG. 11, theprocessor in the memory evaluation apparatus may generate acorresponding tap/click operation instruction, and instruct the displayto display an MC interface 50 that includes a window 511 and that isshown in FIG. 13, where the window 511 displays a “quantity of chargingtimes-failure rate” curve. The “quantity of charging times-failure rate”curve shown in FIG. 13 is a curve that describes how a value of afailure rate parameter of a memory named “DIMM000” changes with a valueof a running parameter that is a quantity of charging/discharging timesof the memory. The MC interface 50 shown in FIG. 13 further includes a“determine” option 512. The “determine” option 512 is further used by auser to determine the “quantity of charging/discharging times-failurerate” curve, so that the display displays the MC interface 50 shown inFIG. 11.

Similarly, the “quantity of charging times-failure rate” curve shown inFIG. 13 may be a curve that is for the memory named “DIMM000” and thatis obtained by the memory evaluation apparatus through matching from aplurality of curves for different memories, and the plurality of curvesfor different memories are stored in the memory evaluation apparatus.Specifically, the memory evaluation apparatus may autonomously obtainthe foregoing “quantity of charging/discharging times-failure rate”curve through matching based on an inherent parameter of the memorynamed “DIMM000”, for example, a parameter such as a memory capacity.

It may be figured out that the memory evaluation apparatus provided inthis embodiment of the present application may alternatively store a“total running duration-failure rate” curve for a factor 3, a “quantityof swap times-failure rate” curve for a factor 4, a “quantity ofCEs-failure rate” curve or a “CE frequency-failure rate” curve for afactor 5, a “quantity of UCEs-failure rate” curve or a “CEfrequency-failure rate” curve for a factor 6, and a “performance valueattenuation magnitude-failure rate” curve for a factor 7. In thisembodiment of the present application, for detailed descriptions ofdisplaying corresponding curves in the MC interface after tap/clickoperations are performed on “set” options corresponding to the factor 3to the factor 7, reference may be made to related descriptions of thefactor 1 and the factor 2 in the foregoing embodiment. Details are notdescribed in this embodiment of the present application.

It should be noted that the memory evaluation apparatus provided in thisembodiment of the present application stores data that describes arelationship between a running parameter and a failure rate parameterthat correspond to each health degree influencing factor, for example, acurve that describes how the failure rate parameter of theto-be-evaluated memory changes with the corresponding running parameter.The curve that describes how the failure rate parameter of theto-be-evaluated memory changes with the corresponding running parameteris data pre-obtained through statistics collection. In this way, thememory evaluation apparatus can evaluate, based on existing dataobtained through statistics collection, a health degree of theto-be-evaluated memory that is not yet faulty.

In a specific embodiment, the health degree evaluation model of theto-be-evaluated memory provided in the embodiments of the presentapplication may include a first submodel that corresponds to each healthdegree influencing factor and a second submodel. A first submodel of onehealth degree influencing factor is a relationship between a healthdegree impairment value corresponding to the health degree influencingfactor and a running parameter and memory failure rate parametercorresponding to the health degree influencing factor. The secondsubmodel is a relationship between the health degree of theto-be-evaluated memory and the health degree impairment valuecorresponding to each health degree influencing factor and arelationship between the health degree of the to-be-evaluated memory andthe weight corresponding to each health degree influencing factor.

Specifically, in the memory evaluation method provided in theembodiments of the present application, step 403 may include step 403 aand step 403 b. For example, step 403 in a flowchart of a memoryevaluation method shown in FIG. 14 may include step 403 a and step 403b.

S403 a: The memory evaluation apparatus separately matches a runningparameter value corresponding to each health degree influencing factorto a first submodel of the corresponding health degree influencingfactor in the health degree evaluation model, to obtain a health degreeimpairment value corresponding to each health degree influencing factor.

For example, step 403 a may be performed by the processor 111 in thememory evaluation apparatus 20 shown in FIG. 2 a.

The running parameter value corresponding to each health degreeinfluencing factor of the to-be-evaluated memory may be obtained in realtime by the memory evaluation apparatus. The health degree impairmentvalue corresponding to each health degree influencing factor is used toindicate a result of impact of the health degree influencing factor onthe health degree of the to-be-evaluated memory.

It should be noted that the first submodel provided in this embodimentof the present application may include the curve in the window 511 inthe MC interface shown in FIG. 12 or FIG. 13.

For example, when the to-be-evaluated memory is the memory named“DIMM000”, and a health degree influencing factor corresponding to theto-be-evaluated memory is the factor 1, the memory evaluation apparatusmay obtain, by referring to an existing “temperature-failure rate”curve, for example, the “temperature-failure rate” curve in the window511 shown in FIG. 12, a failure rate corresponding to each of the atleast one running parameter value, and accumulate running duration toobtain a health degree impairment value (denoted as P₁) of theto-be-evaluated memory for the factor 1. For example, the at least onerunning parameter value of the to-be-evaluated memory is a runningtemperature value T₁, a running temperature value T₂, . . . , and arunning temperature T_(n), where n is a positive integer. In addition,running duration of the to-be-evaluated memory is t_(1_1) when a runningtemperature is T₁, running duration of the to-be-evaluated memory ist_(1_2) when a running temperature is T₂, and running duration of theto-be-evaluated memory is t_(1_n) when a running temperature is T_(n).In this case, with reference to data shown by the “temperature-failurerate” curve in FIG. 12, that is, a failure rate is P_(1_1) when therunning temperature value is T₁, a failure rate is P_(1_2) when therunning temperature value is T₂, and a failure rate is P_(1_n) when therunning temperature value is T_(n), the health degree impairment valueof the to-be-evaluated memory for the factor 1 is

${P_{1} = \frac{{P_{1\_ 1} \times t_{1\_ 1}} + {P_{1\_ 2} \times t_{1\_ 2}} + \ldots + {P_{1{\_ n}} \times t_{1{\_ n}}}}{t_{1\_ 1} + t_{1\_ 2} + \ldots + t_{1{\_ n}}}},$

where T₁, T₂, T_(n), t_(1_1), t_(1_2), and t_(1_n) are all positivenumbers.

For example, when the to-be-evaluated memory is the memory named“DIMM000”, and a health degree influencing factor corresponding to theto-be-evaluated memory is the factor 2, the memory evaluation apparatusmay obtain, by referring to an existing “quantity ofcharging/discharging times-failure rate” curve, for example, the“quantity of charging/discharging times-failure rate” curve in thewindow 511 shown in FIG. 13, a failure rate corresponding to the atleast one running parameter value, and accumulate running duration toobtain a health degree impairment value (denoted as P₂) of theto-be-evaluated memory for the factor 2. For example, the at least onerunning parameter value of the to-be-evaluated memory is a quantity N₁of charging/discharging times, a quantity N₂ of charging/dischargingtimes, . . . , and a quantity N_(n) of charging/discharging times, wheren is a positive integer. In addition, a quantity of charging/dischargingtimes of the to-be-evaluated memory in a time whose duration is t_(2_1)is N₁, a quantity of charging/discharging times of the to-be-evaluatedmemory in a time whose duration is t_(2_2) is N₂, and a quantity ofcharging/discharging times of the to-be-evaluated memory in a time whoseduration is t_(2_n) is N_(n). In this case, with reference to data shownby the “temperature-failure rate” curve in FIG. 13, that is, a failurerate is P_(2_1) when a value of the quantity of charging/dischargingtimes is N₁, a failure rate is P_(2_2) when a value of the quantity ofcharging/discharging times is N₂, and a failure rate is P_(2_n) when avalue of the quantity of charging/discharging times is N_(n), the healthdegree impairment value of the to-be-evaluated memory for the factor 2is

${P_{2} - \frac{{P_{2\_ 1} \times t_{2\_ 1}} + {P_{2\_ 2} \times t_{2\_ 2}} + \ldots + {P_{2{\_ n}} \times t_{2{\_ n}}}}{t_{2\_ 1} + t_{2\_ 2} + \ldots + t_{2{\_ n}}}},$

where N₁, N₂, N_(n), t_(2_1), t_(2_2), and t_(2_n) are all positivenumbers.

For example, when the to-be-evaluated memory is the memory named“DIMM000”, and a health degree influencing factor corresponding to theto-be-evaluated memory is the factor 3, the memory evaluation apparatusmay obtain, by referring to an existing “total running duration-failurerate” curve, a failure rate corresponding to the at least one runningparameter value, and obtain a health degree impairment value (denoted asP₃) of the to-be-evaluated memory for the factor 3. For example, the atleast one running parameter value of the to-be-evaluated memory is totalrunning duration L₁. In addition, a failure rate is P_(3_1) when a valueof the total running duration of the to-be-evaluated memory provided inthe “total running duration-failure rate” curve is L₁. In this case, thehealth degree impairment value of the to-be-evaluated memory for thefactor 3 is P₃=P_(3_1), and L₁ is a positive number.

For example, when the to-be-evaluated memory is the memory named“DIMM000”, and a corresponding health degree influencing factor is thefactor 4, the memory evaluation apparatus may obtain, by referring to anexisting “quantity of swap times-failure rate” curve, a failure ratecorresponding to the at least one running parameter value, and obtain ahealth degree impairment value (denoted as P₄) of the to-be-evaluatedmemory for the factor 4. For example, the at least one running parametervalue of the to-be-evaluated memory is a quantity M₁ of swap times. Inaddition, a failure rate is P_(4_1) when a value of the quantity of swaptimes of the to-be-evaluated memory provided in the “quantity of swaptimes-failure rate” curve is M₁. In this case, the health degreeimpairment value of the to-be-evaluated memory for the factor 4 isP₄=P_(4_1), and M₁ is a positive number.

For example, when the to-be-evaluated memory is the memory named“DIMM000”, and a health degree influencing factor corresponding to theto-be-evaluated memory is the factor 5, the memory evaluation apparatusmay obtain, by referring to an existing “quantity of CEs-failure rate”curve, a failure rate corresponding to the at least one runningparameter value, accumulate running duration, and then obtain, withreference to a change rate of each running parameter value, a healthdegree impairment value (denoted as P₅) of the to-be-evaluated memoryfor the factor 5. For example, the at least one running parameter valueof the to-be-evaluated memory is a quantity F₁ of CEs, a quantity F₂ ofCEs, . . . , and a quantity F_(n) of CEs. In addition, a quantity of CEsof the to-be-evaluated memory in the first time period whose duration ist_(5_1) is F₁, a quantity of CEs in the second time period whoseduration is t_(5_1) is F₂, a quantity of CEs in the n^(th) time periodwhose duration is t_(5_1) is F_(n), where n is a positive integer. Thememory evaluation apparatus collects, at a specific time interval,statistics on the quantity of CEs of the to-be-evaluated memory. Inaddition, a failure rate is P_(5_1) when a value of the quantity of CEsof the to-be-evaluated memory provided in the “quantity of CEs-failurerate” curve is F₁, a failure rate is P_(5_2) when a value of thequantity of CEs is F₂, and a failure rate is P_(5_n) when a value of thequantity of CEs is F_(n). In addition, a change rate of the at least onerunning parameter value, that is, the quantity F₁ of CEs, the quantityF₂ of CEs, . . . , and the quantity F_(n) of CEs, may be denoted as k₁,where k₁ is a positive number greater than 0. In this case, the healthdegree impairment value of the to-be-evaluated memory for the factor 5is

${P_{5} = {k_{1} \times \frac{P_{5\_ 1} + P_{5\_ 2} + \ldots + P_{5{\_ n}}}{n}}},$

and F₁, F₂, F_(n), and t_(5_1) are all positive numbers.

For example, when the to-be-evaluated memory is the memory named“DIMM000”, and a health degree influencing factor corresponding to theto-be-evaluated memory is the factor 6, the memory evaluation apparatusmay obtain, by referring to an existing “quantity of UCEs-failure rate”curve, a failure rate corresponding to the at least one runningparameter value, to obtain a health degree impairment value (denoted asP₆) of the to-be-evaluated memory for the factor 6. In addition, afailure rate is P_(6_1) when a value of the quantity of UCEs of theto-be-evaluated memory provided in the “quantity of UCEs-failure rate”curve is W₁. In this case, the health degree impairment value of theto-be-evaluated memory for the factor 6 is P₆=P_(6_1), and W₁ is apositive integer.

For example, when the to-be-evaluated memory is the memory named“DIMM000”, and a health degree influencing factor corresponding to theto-be-evaluated memory is the factor 7, the memory evaluation apparatusmay obtain, by referring to an existing “performance value attenuationmagnitude-failure rate” curve, a failure rate corresponding to the atleast one running parameter value, and then obtain, with reference to achange rate of each running parameter value, a health degree impairmentvalue (denoted as P₇) of the to-be-evaluated memory for the factor 7.For example, the at least one running parameter value of theto-be-evaluated memory is a performance value attenuation magnitude Y₁,a performance value attenuation magnitude Y₂, . . . , and a performancevalue attenuation magnitude Y_(n), where n is a positive integer. Inaddition, a value of the performance value attenuation magnitude of theto-be-evaluated memory in the first time period whose duration ist_(7_1) is Y₁, a value of the performance value attenuation magnitude ofthe to-be-evaluated memory in the second time period whose duration ist_(7_1) is Y₂, and a value of the performance value attenuationmagnitude of the to-be-evaluated memory in the n^(th) time period whoseduration is t_(7_1) is Y_(n), where n is a positive integer. To bespecific, the memory evaluation apparatus collects, at a specific timeinterval, statistics on a performance value and the performance valueattenuation magnitude of the to-be-evaluated memory. In this case, afailure rate is P_(7_1) when the value of the performance valueattenuation magnitude of the to-be-evaluated memory provided in the“performance value attenuation magnitude-failure rate” curve is Y₁, afailure rate is P_(7_2) when the value of the performance valueattenuation magnitude is Y₂, and a failure rate is P_(7_n) when thevalue of the performance value attenuation magnitude is Y_(n). Inaddition, a change rate of the at least one running parameter, that is,the performance value attenuation magnitude Y₁, the performance valueattenuation magnitude Y₂, . . . , and the performance value attenuationmagnitude Y_(n), may be denoted as k₂, where k₂ is a positive numbergreater than 0. The health degree impairment value of theto-be-evaluated memory for the factor 7 is

${P_{7} = {k_{2} \times \frac{P_{7\_ 1} + P_{7\_ 2} + \ldots + P_{7{\_ n}}}{n}}},$

where Y₁, Y₂, Y_(n), and t_(7_1) are all positive numbers.

S403 b: The memory evaluation apparatus obtains the health degree of theto-be-evaluated memory based on the health degree impairment valuecorresponding to each health degree influencing factor, the weightcorresponding to each health degree influencing factor, and the secondsubmodel.

For example, step 403 b may be performed by the processor 111 in thememory evaluation apparatus 20 shown in FIG. 2 a.

In this embodiment of the present application, the memory evaluationapparatus may obtain, based on the first submodel that corresponds toeach health degree influencing factor in the health degree evaluationmodel, the health degree impairment value that is of the to-be-evaluatedmemory and that corresponds to each health degree influencing factor, toindicate impact of each health degree influencing factor on the healthdegree of the to-be-evaluated memory. In addition, the health degreeimpairment value corresponding to each health degree influencing factorand a weight corresponding to the health degree influencing factor areseparately matched to the second submodel, to obtain the health degreeof the to-be-evaluated memory affected by health degree influencingfactors corresponding to different weights (different weights). In thisway, different health degree evaluation models can be generated fordifferent to-be-evaluated memories. This helps to increase accuracy ofthe health degree that is of the to-be-evaluated memory and that isobtained based on the health degree evaluation model.

In a possible implementation, each of the at least one health degreeinfluencing factor included in the health degree evaluation modelcorresponds to one algorithm, where the algorithm may be addition and/ormultiplication. The memory evaluation apparatus obtains the healthdegree of the to-be-evaluated memory based on the health degreeimpairment value corresponding to each health degree influencing factor,the weight corresponding to each health degree influencing factor, thesecond submodel, and the algorithm corresponding to each health degreeinfluencing factor.

For example, FIG. 15 shows another MC interface according to anembodiment of the present application. Each of at least one healthdegree influencing factor included in the MC interface 50 shown in FIG.15 corresponds to one “algorithm” option. For example, a factor 1 shownin FIG. 15 corresponds to an “algorithm” option 58.

Specifically, when an algorithm corresponding to each health degreeinfluencing factor of a to-be-evaluated memory is addition, a memoryevaluation apparatus multiplies each of at least one health degreeimpairment value of the to-be-evaluated memory by a corresponding weightbased on a second model, to obtain at least one health degree componentof the to-be-evaluated memory, and accumulate the at least one healthdegree component to obtain a health degree of the to-be-evaluatedmemory. For example, the at least one health degree influencing factorcorresponding to the to-be-evaluated memory includes the factor 1, afactor 2, and a factor 5, and weights of the factor 1, the factor 2, andthe factor 5 are respectively 20%, 5%, and 10%. A health degreecomponent (denoted as H₁) corresponding to the factor 1 in the at leastone health degree component is H₁=P₁×20%, a health degree component(denoted as H₂) corresponding to the factor 2 is H₂=P₂×5%, and a healthdegree component (denoted as H₅) corresponding to the factor 5 isH₅=P₅×10%. In this case, the health degree (denoted as H) of theto-be-evaluated memory is H=P₁+P₂+P₅.

When an algorithm corresponding to one health degree influencing factorof the to-be-evaluated memory is multiplication, that the memoryevaluation apparatus obtains the health degree of the to-be-evaluatedmemory based on a health degree impairment value corresponding to eachhealth degree influencing factor, the weight corresponding to eachhealth degree influencing factor, and the second submodel includes thatthe memory evaluation apparatus uses a health degree impairment value ofthe to-be-evaluated memory as the health degree of the to-be-evaluatedmemory based on the second model. For example, for the to-be-evaluatedmemory, if an algorithm corresponding to a factor 3 is multiplication,the health degree of the to-be-evaluated memory is H=H₃=P₃, where H₃ isa health degree component corresponding to the factor 3 ofto-be-evaluated memory, and P₃ is a health degree impairment valuecorresponding to the factor 3 of to-be-evaluated memory.

It should be noted that, in addition to the addition and themultiplication, the algorithm corresponding to the health degreeinfluencing factor in a health degree evaluation model provided in thisembodiment of the present application may alternatively be anotheralgorithm, for example, an integration algorithm. For specificdescription that the algorithm corresponding to the health degreeinfluencing factor provided in this embodiment of the presentapplication is the integration algorithm, reference may be made torelated description in the foregoing embodiment that the algorithmcorresponding to the health degree influencing factor is the addition.Details are not described herein.

For one memory in the memory evaluation apparatus, that is, one memoryin a server, while quantizing impact of each health degree influencingfactor on a health degree of the memory based on a weight correspondingto each the health degree influencing factor of the memory, the memoryevaluation apparatus may further quantize an impact extent of each thehealth degree influencing factor on the health degree of the memorybased on an algorithm corresponding to each health degree influencingfactor. This helps to increase accuracy of the health degree of theto-be-evaluated memory.

In a specific embodiment, the health degree evaluation model of theto-be-evaluated memory provided in the embodiments of the presentapplication includes a first submodel that corresponds to each healthdegree influencing factor and a second submodel. Therefore, that thememory evaluation apparatus determines the health degree evaluationmodel of the to-be-evaluated memory is specifically determining thefirst submodel that corresponds to each health degree influencing factorin the health degree evaluation model and the second submodel of theto-be-evaluated memory. Specifically, in the memory evaluation methodprovided in this embodiment of the present application, step 401includes step 401 a to step 401 e. For example, FIG. 16 is a schematicflowchart of another memory evaluation method according to an embodimentof the present application. In the method shown in FIG. 16, step 401 inFIG. 4 may include step 401 a to step 401 e.

S401 a: The memory evaluation apparatus receives the at least one healthdegree influencing factor that is set by a user.

For example, step 401 a may be performed by the communications interface114 in the memory evaluation apparatus 20 shown in FIG. 2 a.

It should be noted that the at least one health degree influencingfactor is preset in the health degree evaluation model provided in thisembodiment of the present application, and the user may select a healthdegree influencing factor for the to-be-evaluated memory from the atleast one preset health degree influencing factor.

Specifically, referring to the MC interface shown in FIG. 15 in theforegoing embodiment, the MC interface 50 includes the factor 1 to afactor 7. For the to-be-evaluated memory (a memory named “DIMM000”), theuser may perform a tap/click operation on a “close” option correspondingto each factor in the MC interface 50 by using an input device, andselect the at least one health influencing factor corresponding to theto-be-evaluated memory from the factor 1 to the factor 7.

S401 b: The memory evaluation apparatus determines the at least onehealth degree influencing factor that is set by the user, as a healthdegree influencing factor included in the health degree evaluation modelof the to-be-evaluated memory.

For example, step 401 b may be performed by the processor 111 in thememory evaluation apparatus 20 shown in FIG. 2 a.

A processor in the memory evaluation apparatus may receive a tap/clickoperation instruction from the input device, and determine the at leastone health degree influencing factor of the to-be-evaluated memory.

For example, for the to-be-evaluated memory (the memory named“DIMM000”), the user may perform a tap/click operation, by using theinput device, on a “close” option corresponding to each of a factor 5 toa factor 7 in the MC interface 50 shown in FIG. 5. The processor in thememory evaluation apparatus may generate a corresponding tap/clickoperation instruction, and determine that the at least one health degreeinfluencing factor of the to-be-evaluated memory is the factor 1 to afactor 4.

S401 c: The memory evaluation apparatus determines a corresponding firstsubmodel based on the at least one health degree influencing factor.

For example, step 401 c may be performed by the processor 111 in thememory evaluation apparatus 20 shown in FIG. 2 a.

A first submodel of each of the at least one health degree influencingfactor provided in the foregoing embodiment includes data of arelationship between a running parameter corresponding to the healthdegree influencing factor and a failure rate parameter, for example, acurve that describes how a failure rate parameter of the to-be-evaluatedmemory changes with a running parameter corresponding to each healthdegree influencing factor.

For one health degree influencing factor, the health degree evaluationmodel provided in this embodiment of the present application may includea curve that describes how values of a plurality of failure rateparameters (failure rates) change with values of running parameterscorresponding to the health degree influencing factor. To be specific,one first submodel includes the curve that describes how the values ofthe plurality of failure rates change with the values of the runningparameters corresponding to the health degree influencing factor.

It should be noted that the memory evaluation apparatus may autonomouslyobtain, through matching, the curve that describes how the failure rateof the to-be-evaluated memory change with the running parametercorresponding to each health degree influencing factor based on aninherent parameter (for example, a parameter such as a memory capacity)of the to-be-evaluated memory, or the user may select a correspondingcurve from a plurality of curves included in the first submodel of onehealth degree influencing factor.

For example, FIG. 17 is a schematic diagram of another MC interfaceaccording to an embodiment of the present application. Referring to theMC interface 50 shown in FIG. 12, an MC interface 50 shown in FIG. 17further includes an option 513 that allows a user to select a“temperature-failure rate curve 1”. The option 513 includes a “▾”option, and the “▾” option may correspond to a drop-down window. After atap/click operation is performed on the “▾” option in the option 513included in the MC interface 50 shown in FIG. 17, a processor in amemory evaluation apparatus may generate a corresponding tap/clickoperation instruction, and instruct a display to display an MC interface50 that includes a window 5131 and that is shown in FIG. 18. The window5131 includes seven options: a “temperature-failure rate curve 1”option, a “temperature-failure rate curve 2” option, a“temperature-failure rate curve 3” option, a “temperature-failure ratecurve 4” option, a “temperature-failure rate curve 5” option, a“temperature-failure rate curve 6” option, and a “temperature-failurerate curve 7”.

It may be figured out that, after a user performs a tap/click operationon the “temperature-failure rate curve 1” option in the drop-down window5131 corresponding to the option 513 shown in the MC interface 50 shownin FIG. 18, a processor in a memory evaluation apparatus may generate acorresponding tap/click operation instruction, and instruct a display todisplay the MC interface 50 shown in FIG. 17. In addition, the MCinterface 50 shown in FIG. 18 and FIG. 19 further includes a “cancel”option 514. The “cancel” option 514 is used to cancel the“temperature-failure rate curve 1” option selected by the user.

S401 d: The memory evaluation apparatus receives a weight and analgorithm that are set by the user and that correspond to each of the atleast one health degree influencing factor.

For example, step 401 c may be performed by the communications interface114 in the memory evaluation apparatus 20 shown in FIG. 2 a.

The foregoing algorithm includes addition and/or multiplication.Certainly, the foregoing algorithm may alternatively be an integrationalgorithm or the like. In this embodiment of the present application,only an example in which the foregoing algorithm is the addition and/orthe multiplication is used to describe the memory evaluation method inthis embodiment of the present application.

For example, FIG. 19 is a schematic diagram of another MC interfaceaccording to an embodiment of the present application. Referring to theMC interface 50 shown in FIG. 10, a weight corresponding to each healthdegree influencing factor in an MC interface 50 shown in FIG. 19 may beset by a user by using an input device. Referring to the MC interface 50shown in FIG. 15, an algorithm option corresponding to each healthdegree influencing factor in the MC interface 50 shown in FIG. 19further includes a “▾” option, and the “▾” option corresponds to onedrop-down window. For example, the user performs a tap/click operationon a “▾” option in an option 58 corresponding to a factor 1 in the MCinterface 50 shown in FIG. 19. A processor in a memory evaluationapparatus may generate a corresponding tap/click operation instruction,and instruct a display to display a drop-down window 581 in an MCinterface 50 shown in FIG. 20. Specifically, after the user performs atap/click operation on an “addition” option in the drop-down window 581corresponding to the option 58 shown in the MC interface 50 shown inFIG. 20, a processor in a memory evaluation apparatus may generate acorresponding tap/click operation instruction, and instruct a display todisplay the MC interface 50 shown in FIG. 19.

S401 e: The memory evaluation apparatus determines a second submodelbased on the weight and the algorithm that correspond to each healthdegree influencing factor.

For example, step 401 c may be performed by the processor 111 in thememory evaluation apparatus 20 shown in FIG. 2 a.

Referring to the MC interface 50 shown in FIG. 19, a second submodel ofa memory (the to-be-evaluated memory) named “DIMM000” may be determinedby using a “weight” option and an “algorithm” option that correspond toeach health degree influencing factor shown in the MC interface 50. Theuser may perform tap/click operations, by using the input device, on the“weight” option and the “algorithm” option that correspond to eachhealth degree influencing factor in the MC interface 50 shown in FIG.19, so that the processor in the memory evaluation apparatus generatescorresponding tap/click operation instructions.

It should be noted that, different to-be-evaluated memories may havedifferent health degree influencing factors, and data about how failurerate parameters corresponding to health degree influencing factors ofdifferent to-be-evaluated memories change with corresponding runningparameters may be different. Therefore, health degree evaluation modelscorresponding to different to-be-evaluated memories may be different. Inthe memory evaluation method provided in this embodiment of the presentapplication, the memory evaluation apparatus can determine firstsubmodels corresponding to health degree influencing factors fordifferent to-be-evaluated memories and second submodels for theto-be-evaluated memories, that is, determine the health degreeevaluation models for the different to-be-evaluated memories. In thisway, the health degree evaluation model provided in this embodiment ofthe present application can be proper for the to-be-evaluated memory.This helps to increase accuracy of the health degree, of theto-be-evaluated memory, obtained based on the health degree evaluationmodel.

In a specific embodiment, the at least one health degree influencingfactor in the health degree evaluation model provided in this embodimentof the present application may be selected by the user for differentto-be-evaluated memories. A plurality of curves included in the firstsubmodel that corresponds to each health degree influencing factor inthe health degree evaluation model may also be selected by the user fordifferent to-be-evaluated memories. In addition, due to improvement of amanufacturing process of the memory, a health degree influencing factorof the to-be-evaluated memory and data about how a failure ratecorresponding to the health degree influencing factor changes with acorresponding running parameter may also change. Therefore, in thememory evaluation method provided in this embodiment of the presentapplication, adding, by the user, a health degree influencing factor tothe health degree evaluation model and adding, by the user, a relatedcurve to a first submodel that corresponds to one health degreeinfluencing factor are further supported.

Specifically, in the memory evaluation method provided in thisembodiment of the present application, step 401 a may be replaced withstep 401 a′. For example, FIG. 21 is a schematic flowchart of anothermemory evaluation method according to an embodiment of the presentapplication. In the method shown in FIG. 21, step 401 a shown in FIG. 16may be replaced with step 401 a′.

401 a′: The memory evaluation apparatus receives the at least one healthdegree influencing factor that is set by a user and a running parameterand a failure rate parameter that correspond to each health degreeinfluencing factor.

The running parameter and the failure rate parameter that correspond toeach health degree influencing factor that is set by the user are dataabout how a value of the failure rate parameter changes with a value ofthe running parameter, for example, a curve that describes how the valueof the failure rate parameter changes with the value of the runningparameter.

For example, an MC interface 50 shown in FIG. 22 or FIG. 23 furtherincludes an “add” option 59, and the “add” option 59 is used to add onehealth degree influencing factor to a health degree evaluation model.After a user performs a tap/click operation on the “add” option 59 inthe MC interface 50 shown in FIG. 22 by using an input device, aprocessor in a memory evaluation apparatus may generate a correspondingtap/click operation instruction, and instruct a display to display afactor 8 included in an MC interface 50 shown in FIG. 23, and a “set”option, a “weight” option, an “algorithm” option, and the like thatcorrespond to the factor 8 and that are included in the MC interface 50shown in FIG. 23.

Further, FIG. 24 is a schematic diagram of another MC interfaceaccording to an embodiment of the present application. Referring to theMC interfaces 50 shown in FIG. 17 and FIG. 18, an MC interface 50 shownin FIG. 24 further includes an “add” option 514. The “add” option 514 isused to add a curve that describes how a failure rate changes with acorresponding running parameter to one health degree influencing factorin a health degree evaluation model. For example, after a user performsa tap/click operation on the “add” option 514 in the MC interface 50shown in FIG. 24 by using an input device, a processor in a memoryevaluation apparatus may generate a corresponding tap/click operationinstruction, and instruct a display to display an MC interface 50 shownin FIG. 25. The MC interface 50 shown in FIG. 25 includes a “draw acurve” option and an “import a curve” option. The “draw a curve” optionis used to provide a window for a user to draw a curve that describeshow a failure rate corresponding to one health degree influencing factorof a to-be-evaluated memory changes with a corresponding runningparameter. The “import a curve” option is used to provide a window for auser to import a curve that describes how a failure rate correspondingto one health degree influencing factor of a to-be-evaluated memorychanges with a corresponding running parameter.

It should be noted that, according to the health degree evaluation modelprovided in this embodiment of the present application, the user mayselect a health degree influencing factor of the to-be-evaluated memoryfrom the health degree evaluation model and data (a curve) about how afailure rate corresponding to each health degree influencing factorchanges with a corresponding running parameter, or may add a healthdegree influencing factor of the to-be-evaluated memory to the healthdegree evaluation model and data (a curve) about how a failure ratecorresponding to each health degree influencing factor changes with acorresponding running parameter. Therefore, the health degree evaluationmodel of the to-be-evaluated memory is more proper for theto-be-evaluated memory. This helps to increase accuracy of the healthdegree, of the to-be-evaluated memory, obtained based on the healthdegree evaluation model of the to-be-evaluated memory.

In a specific embodiment, in a process of outputting health degreeindication information of the to-be-evaluated memory based on the healthdegree of the to-be-evaluated memory, the memory evaluation apparatusmay match a value of the health degree of the to-be-evaluated memory toa preset value range, to obtain the health degree indication informationof the to-be-evaluated memory. Specifically, step 404 in the foregoingembodiment may include step 404 a to step 404 c. For example, FIG. 27 isa schematic flowchart of another memory evaluation method according toan embodiment of the present application. In the memory evaluationmethod shown in FIG. 27, step 404 shown in FIG. 4 may include step 404 ato step 404 c.

S404 a: When the value of the health degree of the to-be-evaluatedmemory is within a first preset value range, the memory evaluationapparatus outputs first health degree indication information, where thefirst health degree indication information is used to indicate, to theuser, that the to-be-evaluated memory does not need to be replaced.

S404 b: When the value of the health degree of the to-be-evaluatedmemory is within a second preset value range, the memory evaluationapparatus outputs second health degree indication information, where thesecond health degree indication information is used to indicate, to theuser, that the to-be-evaluated memory is replaceable.

S404 c: When the value of the health degree of the to-be-evaluatedmemory is within a third preset value range, the memory evaluationapparatus outputs third health degree indication information, where thethird health degree indication information is used to indicate, to theuser, that the to-be-evaluated memory needs to be replaced.

For example, the first preset value range may be [75, 100], the secondpreset value range may be [45, 74], and the third preset value range maybe [0, 44]. Certainly, the first preset value range, the second presetvalue range, and the third preset value range may be alternatively otherranges. This is not limited in this embodiment of the presentapplication.

It may be figured out that, according to the memory evaluation methodprovided in this embodiment of the present application, the healthdegree indication information of the to-be-evaluated memory may bedisplayed to the user by using an MC interface displayed by the display.

FIG. 27 is a schematic diagram of another MC interface according to anembodiment of the present application. Referring to the MC interfaceshown in FIG. 3, each memory in the MC interface shown in FIG. 27further corresponds to one “health degree” option 32. Health degreeindication information of a to-be-evaluated memory displayed in the MCinterface is a value of health of the to-be-evaluated memory. Within afirst preset value range, a second preset value range, and a thirdpreset value range, values of health degrees are sequentiallyhighlighted in health degree indication information of theto-be-evaluated memory. For example, a normal font (denoted as a font 1)is used in health degree indication information that is of a memorynamed “DIMM000”, a memory named “DIMM002”, and a memory named “DIMM011”and that is displayed in the MC interface in FIG. 27, to indicate, to auser, that the memory does not need to be replaced. A font (denoted as afont 2) that is more highlighted than the font 1 is used in displayedhealth degree indication information of a memory named “DIMM012”, toindicate, to the user, that the memory is replaceable, to be specific,the memory may not be replaced immediately. A font (denoted as a font 3)that is more highlighted than the font 2 is used in displayed healthdegree indication information of a memory named “DIMM001” and a memorynamed “DIMM010”, to indicate, to the user, that the memory needs to bereplaced immediately.

Optionally, that the font 1, the font 2, and the font 3 are successivelymore highlighted means that the font 1, the font 2, and the font 3 aresuccessively enlarged and bold, or colors of the font 1, the font 2, andthe font 3 are successively black, orange, and red.

Certainly, not only the foregoing highlighted font may be used in thehealth degree indication information that is of the to-be-evaluatedmemory and that is displayed in the MC interface provided in thisembodiment of the present application, but also another manner may beused to highlight the health degree indication information that is ofthe to-be-evaluated memory and that is displayed in the MC interfaceprovided in this embodiment of the present application.

For example, FIG. 28 is a schematic diagram of another MC interfaceaccording to an embodiment of the present application.

When a value of a health degree of a to-be-evaluated memory is within afirst preset value range, health degree indication information that isof the to-be-evaluated memory and that is displayed in the MC interfaceis “healthy”, to indicate, to a user, that the to-be-evaluated memorydoes not need to be replaced. For example, health degree indicationinformation of a memory named “DIMM000”, a memory named “DIMM002”, and amemory named “DIMM011” shown in FIG. 28 is “healthy”.

When a value of a health degree of a to-be-evaluated memory is within asecond preset value range, health degree indication information that isof the to-be-evaluated memory and that is displayed in the MC interfaceis “mediocre”, to indicate, to a user, that the to-be-evaluated memoryis replaceable. In this case, health degree indication information thatis of a memory named “DIMM012” and that is displayed in the MC interfaceis “mediocre”.

When a value of a health degree of a to-be-evaluated memory is within athird preset value range, health degree indication information that isof the to-be-evaluated memory and that is displayed in the MC interfaceis “alarm”, to indicate, to a user, that the to-be-evaluated memoryneeds to be replaced. In this case, health degree indication informationthat is of a memory named “DIMM001” and a memory named “DIMM010” andthat is displayed in the MC interface is “alarm”.

It should be noted that in the memory evaluation method provided in thisembodiment of the present application, in a process of displaying thehealth degree indication information of the to-be-evaluated memory tothe user, the memory evaluation apparatus may display different healthdegree indication information for to-be-evaluated memories withdifferent health degree values. In this way, when the to-be-evaluatedmemory is not faulty and a health degree of the memory is relatively low(a value of the health degree is relatively small), the memoryevaluation apparatus can prompt the user to replace the to-be-evaluatedmemory, so that the to-be-evaluated memory can support normal running ofthe server.

It may be figured out that the first preset value range and the secondpreset value range provided in this embodiment of the presentapplication may alternatively be autonomously set by the user based onexperience. Specifically, the memory evaluation method provided in thisembodiment of the present application may further include step 401′before step 401. For example, FIG. 29 is a schematic flowchart ofanother memory evaluation method according to an embodiment of thepresent application. The memory evaluation method shown in FIG. 29 mayfurther include step 401′ before step 401 shown in FIG. 26.

S401′: The memory evaluation apparatus receives a first preset valuerange, a second preset value range, and a third preset value range thatare set by a user.

For example, step 401′ may be performed by the communications interface114 in the memory evaluation apparatus 20 shown in FIG. 2 a.

FIG. 30 or FIG. 31 shows another MC interface according to an embodimentof the present application. Referring to the MC interface provided inthe foregoing embodiment, the MC interface 50 shown in FIG. 30 and FIG.31 further includes a “first preset value range” option, a “secondpreset value range” option, and a “third preset value range” option, andthe “first preset value range” option, the “second preset value range”option, and the “third preset value range” option are used by the userto set the first preset value range, the second preset value range, andthe third preset value range. For example, values “45 to 74” in the“second preset value range” option included in the MC interface shown inFIG. 30 may be set by the user by using an input device. The processorin the memory evaluation apparatus may generate a correspondinginstruction, and instruct the display to display the MC interface 50shown in FIG. 31. Values “45 to 64” in the “second preset value range”option included in the MC interface 50 shown in FIG. 31.

It should be noted that, according to the memory evaluation methodprovided in this embodiment of the present application, the user can setdifferent preset value ranges for different to-be-evaluated memories, sothat the health degree indication information, of the to-be-evaluatedmemory, obtained by the memory evaluation apparatus based on the presetvalue range is more proper for the to-be-evaluated memory. This helps tomore accurately indicate, to the user, whether the to-be-evaluatedmemory needs to be replaced.

In a specific embodiment, in a running process of the to-be-evaluatedmemory, the memory evaluation apparatus may continuously evaluate thehealth degree of the to-be-evaluated memory. In this case, the user mayupdate the health degree evaluation model of the to-be-evaluated memory,so that the health degree evaluation model is more proper for theto-be-evaluated memory. Specifically, the memory evaluation methodprovided in this embodiment of the present application may furtherinclude step 405 and step 406 after step 404. For example, FIG. 32 is aschematic flowchart of another memory evaluation method according to anembodiment of the present application. The memory evaluation methodshown in FIG. 32 may further include step 405 and step 406 after step404 shown in FIG. 4.

S405: The memory evaluation apparatus receives template data that is ofthe to-be-evaluated memory and that is updated by the user.

For example, step 405 may be performed by the communications interface114 in the memory evaluation apparatus 20 shown in FIG. 2 a.

The template data includes at least one or more of the following: the atleast one health degree influencing factor, a running parametercorresponding to each of the at least one health degree influencingfactor, the weight corresponding to each health degree influencingfactor, an algorithm corresponding to each health degree influencingfactor, a first preset value range, a second preset value range, and athird preset value range.

S406: The memory evaluation apparatus updates the health degreeevaluation model based on the updated template data of theto-be-evaluated memory.

For example, step 406 may be performed by the processor 111 in thememory evaluation apparatus 20 shown in FIG. 2 a.

It should be noted that, for a process in which the memory evaluationapparatus updates the template data of the to-be-evaluated memory andthe health degree evaluation model of the to-be-evaluated memory,reference may be made to related description of determining the healthdegree evaluation model of the to-be-evaluated memory in the foregoingembodiment. Details are not described in this embodiment of the presentapplication.

Because the user can update the health degree evaluation model of theto-be-evaluated memory, so that the health degree evaluation model ismore proper for the to-be-evaluated memory, the health degree, of theto-be-evaluated memory, obtained by the memory evaluation apparatusbased on the updated health degree evaluation model is more proper forthe to-be-evaluated memory. This helps to more accurately indicate, tothe user, whether the to-be-evaluated memory needs to be replaced.

The foregoing mainly describes the solutions provided in the embodimentsof the present application from a perspective of interaction of networkelements. It can be understood that each network element, such as thememory evaluation apparatus, includes a corresponding hardware structureand/or a corresponding software module for executing functions. A personskilled in the art should be easily aware that, with reference to theexamples described in the embodiments disclosed in this specification,units and algorithms steps may be implemented by hardware or acombination of hardware and computer software. Whether a function isperformed by hardware or hardware driven by computer software depends onparticular applications and design constraints of the technicalsolutions. A person skilled in the art may use different methods toimplement the described functions for each particular application, butit should not be considered that the implementation goes beyond thescope of this application.

Modules of the memory evaluation apparatus may be obtained throughdivision based on the method embodiments in the embodiments of thepresent application. For example, modules corresponding to functions maybe obtained through division, or two or more functions may be integratedinto one processing module. The integrated module may be implemented ina form of hardware, or may be implemented in a form of a softwaremodule. It should be noted that, in this embodiment of the presentapplication, division into the modules is exemplary, is merely logicalfunction division, and may be other division in an actualimplementation.

When functional modules corresponding to functions are obtained throughdivision, FIG. 33 is a possible schematic diagram of composition of thememory evaluation apparatus provided in the foregoing embodiment. Asshown in FIG. 33, a memory evaluation apparatus 33 may include adetermining module 331, an obtaining module 332, a matching module 333,and an output module 334.

The determining module 331 is configured to support the memoryevaluation apparatus 33 in performing step 401, step 401 a to step 401e, and step 406 in the foregoing embodiment, and/or is configured foranother process of the technology described in this specification. Theobtaining module 332 is configured to support the memory evaluationapparatus 33 in performing step 402 in the foregoing embodiment, and/oris configured for another process of the technology described in thisspecification. The matching module 333 is configured to support thememory evaluation apparatus 33 in performing step 403, step 403 a, andstep 403 b in the foregoing embodiment, and/or is configured for anotherprocess of the technology described in this specification. The outputmodule 334 is configured to support the memory evaluation apparatus 33in performing step 404 and step 404 a to step 403 c in the foregoingembodiment, and/or is configured for another process of the technologydescribed in this specification.

In a possible implementation, FIG. 34 is another possible schematicdiagram of composition of the memory evaluation apparatus provided inthe foregoing embodiment. In a memory evaluation apparatus 33 shown inFIG. 34, the determining module 331 may include a receiving submodule3311 and a determining submodule 3312. The receiving submodule 3311 isconfigured to support the memory evaluation apparatus 33 in performingstep 401 a, step 401 d, step 401′, and step 405 in the foregoingembodiment, and/or is configured for another process of the technologydescribed in this specification. The determining submodule 3312 isconfigured to support the memory evaluation apparatus 33 in performingstep 401 a, step 401 b, step 401 c, step 401 e, and step 406 in theforegoing embodiment, and/or is configured for another process of thetechnology described in this specification.

When an integrated unit is used, the obtaining module 332, a matchingmodule 333, and the determining submodule 3312 may be integrated intoone processing module. The processing module may be a processor or acontroller, for example, a CPU, a general-purpose processor, a digitalsignal processor (DSP), an application-specific integrated circuit(ASIC), a field programmable gate array (FPGA) or another programmablelogic device, transistor logic device, hardware component, or anycombination thereof. The processing module may implement or executevarious illustrations logical blocks, modules, and circuits describedwith reference to content disclosed in the present application. Theprocessing element may alternatively be a combination implementing acomputing function, for example, a combination of one or moremicroprocessors, or a combination of the DSP and a microprocessor. Theoutput module 334 and the receiving submodule 3311 may be implemented bya processor and a communications interface. The output module mayspecifically include a generation submodule and an output submodule. Thegeneration submodule may be configured to generate health degreeindication information of a to-be-evaluated memory, and the outputsubmodule may be configured to output the health degree indicationinformation of the to-be-evaluated memory by using a display.

The storage module may be a memory. Certainly, the memory evaluationapparatus 33 may further include another functional module.

With reference to the memory evaluation apparatus shown in FIG. 2a inthe foregoing embodiment, the processing module may be the processor 111shown in FIG. 2 a. The storage module may be the hard disk 112 and theat least one memory 113 shown in FIG. 2 a. The communications module maybe the communications interface 114 shown in FIG. 2 a. Thecommunications bus 114 may specifically be a peripheral componentinterconnect (PCI) bus, an extended industry standard architecture(EISA) bus, or the like. The communications bus 114 may be classifiedinto an address bus, a data bus, a control bus, and the like. This isnot limited in this embodiment of the present application.

It should be noted that, for detailed descriptions of the modules in thememory evaluation apparatus 33 provided in this embodiment of thepresent application and technical effects brought after the modulesperform related method steps in the foregoing embodiment, reference maybe made to related descriptions in the method embodiment of the presentapplication. Details are not described herein.

The foregoing descriptions about implementations allow a person skilledin the art to clearly understand that, for the purpose of convenient andbrief description, only division into the foregoing functional modulesis taken as an example for illustration. In actual application, theforegoing functions can be allocated to different functional modules andimplemented by the different functional modules based on a requirement,to be specific, an inner structure of an apparatus is divided intodifferent functional modules to implement all or some of the functionsdescribed above. For a detailed working process of the foregoing system,apparatus, and unit, reference may be to a corresponding process in theforegoing method embodiments, and details are not described herein.

In the several embodiments provided in this application, it should beunderstood that the disclosed system, apparatus, and method may beimplemented in other manners. For example, the described apparatusembodiment is merely an example. For example, the division into themodules or units is merely logical function division and may be otherdivision in actual implementation. For example, a plurality of units orcomponents may be combined or integrated into another system, or somefeatures may be ignored or not performed. In addition, the displayed ordiscussed mutual couplings or direct couplings or communicationconnections may be implemented through some interfaces. The indirectcouplings or communication connections between the apparatuses or unitsmay be implemented in electronic, mechanical, or other forms.

The units described as separate parts may or may not be physicallyseparate, and parts displayed as units may or may not be physical units,may be located in one position, or may be distributed on a plurality ofnetwork units. Some or all of the units may be selected based on actualrequirements to achieve the objectives of the solutions of theembodiments.

In addition, functional units in the embodiments of this application maybe integrated into one processing unit, or each of the units may existalone physically, or two or more units are integrated into one unit. Theintegrated unit may be implemented in a form of hardware, or may beimplemented in a form of a software functional unit.

When the integrated unit is implemented in the form of a softwarefunctional unit and sold or used as an independent product, theintegrated unit may be stored in a computer-readable storage medium.Based on such an understanding, the technical solutions of thisapplication essentially, or the part contributing to the prior art, orall or some of the technical solutions may be implemented in the form ofa software product. The computer software product is stored in a storagemedium and includes several instructions for instructing a computerdevice (which may be a personal computer, a server, a network device, orthe like) or a processor to perform all or some of the steps of themethods described in the embodiments of this application. The foregoingstorage medium includes: any medium that can store program code, such asa flash memory, a removable hard disk, a read-only memory, a randomaccess memory, a magnetic disk, or an optical disc.

The foregoing descriptions are merely specific implementations of thisapplication, but are not intended to limit the protection scope of thisapplication. Any variation or replacement within the technical scopedisclosed in this application shall fall within the protection scope ofthis application. Therefore, the protection scope of this applicationshall be subject to the protection scope of the claims.

1. A memory evaluation method, comprising: determining a health degreeevaluation model of a memory, wherein in the health degree evaluationmodel, a health degree of the memory changes with at least one healthdegree influencing factor of the memory, each health degree influencingfactor corresponds to a running parameter, and each health degreeinfluencing factor corresponds to a weight; obtaining at least onerunning parameter value of each running parameter corresponding to eachof the at least one health degree influencing factor; obtaining thehealth degree of the memory by matching the at least one runningparameter value of each running parameter corresponding to each healthdegree influencing factor to the health degree evaluation model; andindicating whether the memory needs to be replaced, based on the healthdegree of the memory.
 2. The method according to claim 1, wherein theobtaining the health degree of the memory by matching the at least onerunning parameter value of each running parameter corresponding to eachhealth degree influencing factor to the health degree evaluation modelcomprises: matching the at least one running parameter value of eachrunning parameter corresponding to each health degree influencing factorto a first submodel of the corresponding health degree influencingfactor in the health degree evaluation model, to obtain a health degreeimpairment value corresponding to each health degree influencing factor,wherein the health degree evaluation model comprises a second submodeland the first submodel that corresponds to each health degreeinfluencing factor, the first submodel of one health degree influencingfactor is a relationship between a health degree impairment valuecorresponding to the health degree influencing factor and the runningparameter and a failure rate parameter corresponding to the healthdegree influencing factor, and the second submodel is a relationship inwhich the health degree of the memory changes with the health degreeimpairment value corresponding to each health degree influencing factorand a relationship in which the health degree of the memory changes withthe weight corresponding to each health degree influencing factor; andobtaining the health degree of the memory based on the health degreeimpairment value corresponding to each health degree influencing factor,the weight corresponding to each health degree influencing factor, andthe second submodel.
 3. The method according to claim 2, wherein the atleast one health degree influencing factor comprises one or more of thefollowing: a memory running temperature factor, a memory service loadfactor, a total memory running duration factor, a memory swap factor, amemory correctable error (CE) frequency factor, a memory uncorrectableerror UCQ frequency factor, or a memory performance attenuation factor.4. The method according to claim 3, wherein a running parametercorresponding to the memory running temperature factor is a runningtemperature of the memory; a running parameter corresponding to thememory service load factor is a quantity of charging/discharging timesof the memory; a running parameter corresponding to the total memoryrunning duration factor is total running duration of the memory; arunning parameter corresponding to the memory swap factor is a quantityof swap times of the memory; a running parameter corresponding to thememory CE frequency factor is a quantity of CEs of the memory and/or aCE frequency of the memory; a running parameter corresponding to thememory UCE frequency factor is a quantity of UCEs of the memory and/or aUCE frequency of the memory; and a running parameter corresponding tothe memory performance attenuation factor is a performance valueattenuation magnitude of the memory.
 5. The method according to claim 1,wherein the method comprises: outputting first health degree indicationinformation when a value of the health degree of the memory is within afirst preset value range, wherein the first health degree indicationinformation is used to indicate, to the user, that the memory does notneed to be replaced; outputting second health degree indicationinformation when a value of the health degree of the memory is within asecond preset value range, wherein the second health degree indicationinformation is used to indicate, to the user, that the memory isreplaceable; or outputting third health degree indication informationwhen a value of the health degree of the memory is within a third presetvalue range, wherein the third health degree indication information isused to indicate, to the user, that the memory needs to be replaced. 6.The method according to claim 5, wherein the determining the healthdegree evaluation model of the memory comprises: receiving the at leastone health degree influencing factor that is set by the user;determining the at least one health degree influencing factor that isset by the user, as the health degree influencing factor comprised inthe health degree evaluation model of the memory; determining acorresponding first submodel based on the at least one health degreeinfluencing factor; receiving the weight and an algorithm thatcorrespond to each of the at least one health degree influencing factorthat is set by the user, wherein the algorithm comprises addition and/ormultiplication; and determining the second submodel based on the weightand the algorithm that correspond to each health degree influencingfactor.
 7. The method according to claim 6, wherein the receiving the atleast one health degree influencing factor that is set by the usercomprises: receiving the at least one health degree influencing factorthat is set by the user and the running parameter and the failure rateparameter that correspond to each health degree influencing factor. 8.The method according to claim 7, wherein before the health degreeindication information of the memory is generated based on the healthdegree of the memory, the method further comprises: receiving the firstpreset value range, the second preset value range, and the third presetvalue range that are set by the user.
 9. The method according to claim8, wherein after the running parameter value corresponding to eachhealth degree influencing factor is separately input to the healthdegree evaluation model, to obtain the health degree of the memory, themethod further comprises: receiving template data that is of the memoryand that is updated by the user, wherein the template data comprises atleast one or more of the following: the at least one health degreeinfluencing factor, the running parameter corresponding to each of theat least one health degree influencing factor, the weight correspondingto each health degree influencing factor, the algorithm corresponding toeach health degree influencing factor, the first preset value range, thesecond preset value range, and the third preset value range; andupdating the health degree evaluation model based on the updatedtemplate data of the memory.
 10. A memory evaluation apparatus,comprising a processor and a memory, wherein the processor executes aninstruction stored in the memory, so that the memory evaluationapparatus is configured to: determine a health degree evaluation modelof the memory, wherein in the health degree evaluation model, a healthdegree of the memory changes with at least one health degree influencingfactor of the memory, each health degree influencing factor correspondsto a running parameter, and each health degree influencing factorcorresponds to a weight; obtain at least one running parameter value ofeach running parameter corresponding to each of the at least one healthdegree influencing factor; obtain the health degree of the memory bymatching the at least one running parameter value of each runningparameter corresponding to each health degree influencing factor to thehealth degree evaluation model; and indicate whether the memory needs tobe replaced, based on the health degree of the memory.
 11. The apparatusaccording to claim 10, wherein the apparatus is configured to: match theat least one running parameter value of each running parametercorresponding to each health degree influencing factor to a firstsubmodel of the corresponding health degree influencing factor in thehealth degree evaluation model, to obtain a health degree impairmentvalue corresponding to each health degree influencing factor, whereinthe health degree evaluation model comprises a second submodel and thefirst submodel that corresponds to each health degree influencingfactor, the first submodel of one health degree influencing factor is arelationship between a health degree impairment value corresponding tothe health degree influencing factor and the running parameter and afailure rate parameter corresponding to the health degree influencingfactor, and the second submodel is a relationship in which the healthdegree of the memory changes with the health degree impairment valuecorresponding to each health degree influencing factor and arelationship in which the health degree of the memory changes with theweight corresponding to each health degree influencing factor; andobtain the health degree of the memory based on the health degreeimpairment value corresponding to each health degree influencing factor,the weight corresponding to each health degree influencing factor, andthe second submodel.
 12. The apparatus according to claim 11, whereinthe at least one health degree influencing factor comprises one or moreof the following: a memory running temperature factor, a memory serviceload factor, a total memory running duration factor, a memory swapfactor, a memory correctable error (CE) frequency factor, a memoryuncorrectable error (UCE) frequency factor, or a memory performanceattenuation factor.
 13. The apparatus according to claim 12, wherein arunning parameter corresponding to the memory running temperature factoris a running temperature of the memory; a running parametercorresponding to the memory service load factor is a quantity ofcharging/discharging times of the memory; a running parametercorresponding to the total memory running duration factor is totalrunning duration of the memory; a running parameter corresponding to thememory swap factor is a quantity of swap times of the memory; a runningparameter corresponding to the memory CE frequency factor is a quantityof CEs of the memory and/or a CE frequency of the memory; a runningparameter corresponding to the memory UCE frequency factor is a quantityof UCEs of the memory and/or a UCE frequency of the memory; and arunning parameter corresponding to the memory performance attenuationfactor is a performance value attenuation magnitude of the memory. 14.The apparatus according to claim 10, wherein the apparatus is configuredto: output first health degree indication information when a value ofthe health degree of the memory is within a first preset value range,wherein the first health degree indication information is used toindicate, to the user, that the memory does not need to be replaced;output second health degree indication information when a value of thehealth degree of the memory is within a second preset value range,wherein the second health degree indication information is used toindicate, to the user, that the memory is replaceable; or output thirdhealth degree indication information when a value of the health degreeof the memory is within a third preset value range, wherein the thirdhealth degree indication information is used to indicate, to the user,that the memory needs to be replaced.
 15. The apparatus according toclaim 14, wherein the apparatus is configured to: receive the at leastone health degree influencing factor that is set by the user; anddetermine the at least one health degree influencing factor that is setby the user, as the health degree influencing factor comprised in thehealth degree evaluation model of the memory; and determine acorresponding first submodel based on the at least one health degreeinfluencing factor, wherein receive the weight and an algorithm thatcorrespond to each of the at least one health degree influencing factorthat is set by the user, wherein the algorithm comprises addition and/ormultiplication; and determine the second submodel based on the weightand the algorithm that correspond to each health degree influencingfactor.
 16. The apparatus according to claim 15, wherein the apparatusis configured to: receive the at least one health degree influencingfactor that is set by the user and the running parameter and the failurerate parameter that correspond to each health degree influencing factor.17. The apparatus according to claim 16, wherein the apparatus isconfigured to: before the health degree indication information of thememory is generated based on the health degree of the memory, receivethe first preset value range, the second preset value range, and thethird preset value range that are set by the user.
 18. The apparatusaccording to claim 17, wherein the apparatus is configured to: after therunning parameter value corresponding to each health degree influencingfactor to the health degree evaluation model is matched, to obtain thehealth degree of the memory, receive template data that is of the memoryand that is updated by the user, wherein the template data comprises atleast one or more of the following: the at least one health degreeinfluencing factor, the running parameter corresponding to each of theat least one health degree influencing factor, the weight correspondingto each health degree influencing factor, the algorithm corresponding toeach health degree influencing factor, the first preset value range, thesecond preset value range, and the third preset value range; and updatethe health degree evaluation model based on the updated template datathat is of the memory.
 19. A computer storage medium, comprising atleast one instruction, wherein when the at least one instruction is runon a computer, the computer is enabled to perform the memory evaluationmethod of claim 1.